Chunhua Shen

Professor Chunhua Shen

Professor

School of Computer Science

Faculty of Engineering, Computer and Mathematical Sciences

Eligible to supervise Masters and PhD - email supervisor to discuss availability.

He was a Professor of Computer Science at The University of Adelaide from 2014 to Jan. 2021. His research mainly focuses on Machine Learning and Computer Vision; the objective is to build a visual system with human-like performance.

Chunhua Shen is an Adjunct Professor of Data Science and AI at Faculty of Information Technology, Monash University.

From 2014 to Jan. 2021, Chunhua Shen was a Professor of Computer Science at University of Adelaide, leading the Adelaide Machine Learning Group. He held an ARC Future Fellowship from 2012 to 2016.

He received a PhD degree at University of Adelaide; then worked at the NICTA (formerly National ICT Australia) computer vision program for about six years. From 2006 to 2011, he held an adjunct position at College of Engineering & Computer Science, Australian National University. 

A list of published papers :List in PDF, Google scholar, and arXiv.
See git.io/shen for more information.

    Expand

  • Appointments
    Date Position Institution name
    2014 - 2021 Professor University of Adelaide
    2011 - 2014 Senior Lecturer/Associate Professor University of Adelaide
    2005 - 2011 Researcher/Senior Researcher National ICT Australia and Australian National University

  • Awards and Achievements
    Date Type Title Institution Name Country Amount
    2012 Fellowship Australian Research Council Future Fellowship — Australia —

  • Education
    Date Institution name Country Title
    2003 - 2005 University of Adelaide Australia PhD
    — Nanjing University China Master
    — Nanjing University China Bachelor
    — Australian National University Australia MPhil Applied Statistics

  • Research Interests
    Computer Graphics Computer Vision Knowledge Representation and Machine Learning
    Expand

  • Journals
    Year Citation
    2022 Zhao, Y., Yu, X., Gao, Y., & Shen, C. (2022). Learning discriminative region representation for person retrieval. Pattern Recognition, 121, 108229.
    DOI
    2021 Yu, C., Gao, C., Wang, J., Yu, G., Shen, C., & Sang, N. (2021). BiSeNet V2: Bilateral Network with Guided Aggregation for Real-Time Semantic Segmentation. International Journal of Computer Vision, 18 pages.
    DOI
    2021 Wei, X. S., Ye, H. J., Mu, X., Wu, J., Shen, C., & Zhou, Z. H. (2021). Multi-Instance Learning with Emerging Novel Class. IEEE Transactions on Knowledge and Data Engineering, 33(5), 2109-2120.
    DOI Scopus3 WoS2
    2021 Liu, Y., Shen, C., Jin, L., He, T., Chen, P., Liu, C., & Chen, H. (2021). ABCNet v2: Adaptive Bezier-Curve Network for Real-time End-to-end Text Spotting. IEEE Transactions on Pattern Analysis and Machine Intelligence, 1.
    DOI
    2021 Liu, Y., He, T., Chen, H., Wang, X., Luo, C., Zhang, S., . . . Jin, L. (2021). Exploring the Capacity of an Orderless Box Discretization Network for Multi-orientation Scene Text Detection. International Journal of Computer Vision, 129(6), 1972-1992.
    DOI Scopus1 WoS1
    2021 Pang, G., Shen, C., Cao, L., & Hengel, A. V. D. (2021). Deep Learning for Anomaly Detection: A Review. ACM Computing Surveys, 54(2), 1-36.
    DOI Scopus18 WoS17
    2021 Wang, W., Xie, E., Li, X., Liu, X., Liang, D., Zhibo, Y., . . . Shen, C. (2021). PAN++: Towards Efficient and Accurate End-to-End Spotting of Arbitrarily-Shaped Text. IEEE Transactions on Pattern Analysis and Machine Intelligence, 1.
    DOI
    2021 Bian, J. -W., Zhan, H., Wang, N., Li, Z., Zhang, L., Shen, C., . . . Reid, I. (2021). Unsupervised scale-consistent depth learning from video. International Journal of Computer Vision, 129(9), 2548-2564.
    DOI Scopus1 WoS1
    2021 Wang, X., Zhang, R., Shen, C., Kong, T., & Li, L. (2021). SOLO: A Simple Framework for Instance Segmentation. IEEE Transactions on Pattern Analysis and Machine Intelligence, 1.
    DOI
    2021 Tian, L., Wang, P., Liang, G., & Shen, C. (2021). An adversarial human pose estimation network injected with graph structure. Pattern Recognition, 115, 107863.
    DOI Scopus1
    2021 Yin, W., Liu, Y., & Shen, C. (2021). Virtual Normal: Enforcing Geometric Constraints for Accurate and Robust Depth Prediction. IEEE Transactions on Pattern Analysis and Machine Intelligence, 1.
    DOI
    2021 Zhao, Y., Shen, C., Yu, X., Chen, H., Gao, Y., & Xiong, S. (2021). Learning deep part-aware embedding for person retrieval. Pattern Recognition, 116, 1-10.
    DOI Scopus1 WoS1
    2021 Xie, Y., Zhang, J., Lu, H., Shen, C., & Xia, Y. (2021). SESV: Accurate Medical Image Segmentation by Predicting and Correcting Errors. IEEE Transactions on Medical Imaging, 40(1), 286-296.
    DOI Scopus4 WoS3
    2021 Zhang, S., Liu, Y., Jin, L., Wei, Z., & Shen, C. (2021). OPMP: An Omnidirectional Pyramid Mask Proposal Network for Arbitrary-Shape Scene Text Detection. IEEE Transactions on Multimedia, 23, 454-467.
    DOI Scopus3 WoS3
    2021 Luo, C., Lin, Q., Liu, Y., Jin, L., & Shen, C. (2021). Separating Content from Style Using Adversarial Learning for Recognizing Text in the Wild. International Journal of Computer Vision, 129(4), 17 pages.
    DOI Scopus3 WoS1
    2021 Dong, G., Yan, Y., Shen, C., & Wang, H. (2021). Real-Time High-Performance Semantic Image Segmentation of Urban Street Scenes. IEEE Transactions on Intelligent Transportation Systems, 22(6), 3258-3274.
    DOI Scopus7 WoS7
    2021 Zhang, L., Shi, Z., Zhou, J. T., Cheng, M. M., Liu, Y., Bian, J. W., . . . Shen, C. (2021). Ordered or Orderless: A Revisit for Video Based Person Re-Identification. IEEE Transactions on Pattern Analysis and Machine Intelligence, 43(4), 1460-1466.
    DOI Scopus5 WoS17
    2021 Zhuang, B., Tan, M., Liu, J., Liu, L., Reid, I., & Shen, C. (2021). Effective Training of Convolutional Neural Networks with Low-bitwidth Weights and Activations. IEEE Transactions on Pattern Analysis and Machine Intelligence, 1.
    DOI Scopus1
    2021 Zhang, J., Xie, Y., Pang, G., Liao, Z., Verjans, J., Li, W., . . . Xia, Y. (2021). Viral pneumonia screening on chest X-rays using confidence-aware anomaly detection. IEEE Transactions on Medical Imaging, 40(3), 879-890.
    DOI Scopus11 WoS7 Europe PMC18
    2020 Lin, G., Liu, F., Milan, A., Shen, C., & Reid, I. (2020). RefineNet: multi-path refinement networks for dense prediction. IEEE Transactions on Pattern Analysis and Machine Intelligence, 42(5), 1228-1242.
    DOI Scopus12 WoS9 Europe PMC2
    2020 Wang, X., Zhang, R., Kong, T., Li, L., & Shen, C. (2020). SOLOv2: Dynamic and fast instance segmentation. Advances in Neural Information Processing Systems, 2020-December.
    Scopus9
    2020 Gong, D., Zhang, Z., Shi, Q., van den Hengel, A., Shen, C., & Zhang, Y. (2020). Learning deep gradient descent optimization for image deconvolution. IEEE Transactions on Neural Networks and Learning Systems, 31(12), 5468-5482.
    DOI Scopus8 WoS4
    2020 Zhang, L., Wei, W., Shi, Q., Shen, C., van den Hengel, A., & Zhang, Y. (2020). Accurate tensor completion via adaptive low-rank representation. IEEE Transactions on Neural Networks and Learning Systems, 31(1), 4170-4184.
    DOI Scopus1 WoS1
    2020 Zhao, Y., Liu, Y., Shen, C., Gao, Y., & Xiong, S. (2020). MobileFAN: transferring deep hidden representation for face alignment. Pattern Recognition, 100, 10 pages.
    DOI Scopus7 WoS5
    2020 Zhao, Y., Shen, C., Wang, H., & Chen, S. (2020). Structural Analysis of Attributes for Vehicle Re-Identification and Retrieval. IEEE Transactions on Intelligent Transportation Systems, 21(2), 723-734.
    DOI Scopus10 WoS8
    2020 Zhang, P., Liu, W., Wang, D., Lei, Y., Wang, H., Shen, C., & Lu, H. (2020). Non-rigid object tracking via deep multi-scale spatial-temporal discriminative saliency maps. Pattern Recognition, 100, 14 pages.
    DOI Scopus11 WoS10
    2020 Wang, X., Kong, T., Shen, C., Jiang, Y., & Li, L. (2020). SOLO: Segmenting Objects by Locations. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 12363 LNCS, 649-665.
    DOI Scopus11
    2020 Zhang, H., Li, Y., Chen, H., & Shen, C. (2020). Memory-efficient hierarchical neural architecture search for image denoising. Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 3654-3663.
    DOI Scopus5
    2020 Zhang, X., Zhang, R., Cao, J., Gong, D., You, M., & Shen, C. (2020). Part-Guided Attention Learning for Vehicle Instance Retrieval. IEEE Transactions on Intelligent Transportation Systems, 1-13.
    DOI
    2020 Zhuang, B., Liu, L., Tan, M., Shen, C., & Reid, I. (2020). Training quantized neural networks with a full-precision auxiliary module. Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 1485-1494.
    DOI Scopus5 WoS1
    2020 Liu, W., Zhang, P., Chen, X., Shen, C., Huang, X., & Yang, J. (2020). Embedding Bilateral Filter in Least Squares for Efficient Edge-preserving Image Smoothing. IEEE Transactions on Circuits and Systems for Video Technology, 30(1), 23-35.
    DOI Scopus3 WoS2
    2020 Zhang, L., Wang, P., Shen, C., Liu, L., Wei, W., Zhang, Y., & van den Hengel, A. (2020). Adaptive importance learning for improving lightweight image super-resolution network. International Journal of Computer Vision, 128(2), 479-499.
    DOI Scopus9 WoS9
    2020 Chen, Y., Shen, C., Chen, H., Wei, X., Liu, L., & Yang, J. (2020). Adversarial learning of structure-aware fully convolutional networks for landmark localization. IEEE Transactions on Pattern Analysis and Machine Intelligence, 42(7), 1654-1669.
    DOI Scopus6 WoS3 Europe PMC1
    2020 Liu, L., Lu, H., Xiong, H., Xian, K., Cao, Z., & Shen, C. (2020). Counting objects by blockwise classification. IEEE Transactions on Circuits and Systems for Video Technology, 30(10), 3513-3527.
    DOI Scopus3 WoS2
    2020 Zhang, L., Wang, P., Li, H., Li, Z., Shen, C., & Zhang, Y. (2020). A Robust Attentional Framework for License Plate Recognition in the Wild. IEEE Transactions on Intelligent Transportation Systems, 1-10.
    DOI
    2020 Wang, X., Shen, C., Li, H., & Xu, S. (2020). Human Detection Aided by Deeply Learned Semantic Masks. IEEE Transactions on Circuits and Systems for Video Technology, 30(8), 2663-2673.
    DOI Scopus1
    2020 Cao, Y., Zhao, T., Xian, K., Shen, C., Cao, Z., & Xu, S. (2020). Monocular Depth Estimation with Augmented Ordinal Depth Relationships. IEEE Transactions on Circuits and Systems for Video Technology, 30(8), 2674-2682.
    DOI
    2020 Wang, X., Yin, W., Kong, T., Jiang, Y., Li, L., & Shen, C. (2020). Task-aware monocular depth estimation for 3D object detection. AAAI 2020 - 34th AAAI Conference on Artificial Intelligence, 34, 12257-12264.
    Scopus1
    2020 Zhang, L., Wang, P., Liu, L., Shen, C., Wei, W., Zhang, Y., & van den Hengel, A. (2020). Towards Effective Deep Embedding for Zero-Shot Learning. IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS FOR VIDEO TECHNOLOGY, 30(9), 2843-2852.
    DOI Scopus3 WoS2
    2020 Liu, W., Zhang, P., Huang, X., Yang, J., Shen, C., & Reid, I. (2020). Real-time image smoothing via iterative least squares. ACM Transactions on Graphics, 39(3), 28-1-28-24.
    DOI Scopus3 WoS3
    2020 Xie, Y., Zhang, J., Xia, Y., & Shen, C. (2020). A Mutual Bootstrapping Model for Automated Skin Lesion Segmentation and Classification. IEEE Transactions on Medical Imaging, 39(7), 2482-2493.
    DOI Scopus36 WoS23 Europe PMC8
    2020 Liu, L., Lu, H., Zou, H., Xiong, H., Cao, Z., & Shen, C. (2020). Weighing Counts: Sequential Crowd Counting by Reinforcement Learning. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 12355 LNCS, 164-181.
    DOI Scopus1
    2020 Liu, L., Cao, Z., Lu, H., Xiong, H., & Shen, C. (2020). NSSNet: Scale-Aware Object Counting With Non-Scale Suppression. IEEE Transactions on Intelligent Transportation Systems, 1-12.
    DOI
    2020 Dai, Y., Lu, H., & Shen, C. (2020). Towards Light-Weight Portrait Matting via Parameter Sharing. Computer Graphics Forum, 40(1), 14 pages.
    DOI
    2019 Li, H., Wang, P., & Shen, C. (2019). Toward End-to-End Car License Plate Detection and Recognition With Deep Neural Networks. IEEE Transactions on Intelligent Transportation Systems, 20(3), 1126-1136.
    DOI Scopus87 WoS67
    2019 Wei, X., Zhang, C., Wu, J., Shen, C., & Zhou, Z. (2019). Unsupervised object discovery and co-localization by deep descriptor transformation. Pattern Recognition, 88, 113-126.
    DOI Scopus20 WoS17
    2019 Wu, Z., Shen, C., & van den Hengel, A. (2019). Wider or Deeper: Revisiting the ResNet Model for Visual Recognition. Pattern Recognition, 90, 119-133.
    DOI Scopus255 WoS184
    2019 Wang, P., Liu, L., Shen, C., & Shen, H. (2019). Order-aware convolutional pooling for video based action recognition. Pattern Recognition, 91, 357-365.
    DOI Scopus11 WoS11
    2019 Liu, H., Ji, R., Wang, J., & Shen, C. (2019). Ordinal constraint binary coding for approximate nearest neighbor search. IEEE Transactions on Pattern Analysis and Machine Intelligence, 41(4), 941-955.
    DOI Scopus19 WoS20
    2019 Zhang, L., Wang, P., Wei, W., Lu, H., Shen, C., van den Hengel, A., & Zhang, Y. (2019). Unsupervised domain adaptation using robust class-wise matching. IEEE Transactions on Circuits and Systems for Video Technology, 29(5), 1339-1349.
    DOI Scopus14 WoS11
    2019 Yao, R., Lin, G., Shen, C., Zhang, Y., & Shi, Q. (2019). Semantics-Aware Visual Object Tracking. IEEE Transactions on Circuits and Systems for Video Technology, 29(6), 1687-1700.
    DOI Scopus12 WoS10
    2019 Zhang, L., Wei, W., Shi, Q., Shen, C., van den Hengel, A., & Zhang, Y. (2019). Accurate imagery recovery using a multi-observation patch model. Information Sciences, 501, 724-741.
    DOI Scopus1
    2019 Zhang, P., Liu, W., Lu, H., & Shen, C. (2019). Salient object detection with lossless feature reflection and weighted structural loss. IEEE Transactions on Image Processing, 28(6), 3048-3060.
    DOI Scopus30 WoS23
    2019 Zhang, J., Wu, Q., Zhang, J., Shen, C., Lu, J., & Wu, Q. (2019). Heritage image annotation via collective knowledge. Pattern Recognition, 93, 204-214.
    DOI Scopus2 WoS2
    2019 Wei, X., Wang, P., Liu, L., Shen, C., & Wu, J. (2019). Piecewise Classifier Mappings: Learning Fine-Grained Learners for Novel Categories with Few Examples. IEEE Transactions on Image Processing, 28(12), 6116-6125.
    DOI Scopus24 WoS13
    2019 Zhang, J., Xie, Y., Xia, Y., & Shen, C. (2019). Attention residual learning for skin lesion classification. IEEE Transactions on Medical Imaging, 38(9), 2092-2103.
    DOI Scopus104 WoS78
    2019 Zhang, H., Li, Y., Jiang, Y., Wang, P., Shen, Q., & Shen, C. (2019). Hyperspectral classification based on lightweight 3-D-CNN with transfer learning. IEEE Transactions on Geoscience and Remote Sensing, 57(8), 5813-5828.
    DOI Scopus44 WoS39
    2019 Xiong, H., Cao, Z., Lu, H., Madec, S., Liu, L., & Shen, C. (2019). TasselNetv2: in-field counting of wheat spikes with context-augmented local regression networks. Plant Methods, 15(1), 150-1-150-14.
    DOI Scopus22 WoS13 Europe PMC2
    2019 Peng, X., Zhu, H., Feng, J., Shen, C., Zhang, H., & Zhou, J. T. (2019). Deep Clustering With Sample-Assignment Invariance Prior.. IEEE transactions on neural networks and learning systems, 31(11), 4857-4868.
    DOI Scopus49 WoS44 Europe PMC3
    2019 Nekrasov, V., Shen, C., & Reid, I. (2019). Light-weight refinenet for real-time semantic segmentation. British Machine Vision Conference 2018, BMVC 2018, abs/1810.03272.
    Scopus21
    2019 Zhang, T., Lin, G., Cai, J., Shen, T., Shen, C., & Kot, A. (2019). Decoupled Spatial Neural Attention for Weakly Supervised Semantic Segmentation. IEEE Transactions on Multimedia, 21(11), 2930-2941.
    DOI Scopus18 WoS1
    2019 Yan, Y., Huang, Y., Chen, S., Shen, C., & Wang, H. (2019). Joint Deep Learning of Facial Expression Synthesis and Recognition. IEEE Transactions on Multimedia, 22(11), 2792-2807.
    DOI Scopus2 WoS1
    2018 Liu, F., Lin, G., Qiao, R., & Shen, C. (2018). Structured Learning of Tree Potentials in CRF for Image Segmentation. IEEE Transactions on Neural Networks and Learning Systems, 29(6), 2631-2637.
    DOI Scopus9 WoS10
    2018 Wei, X., Xie, C., Wu, J., & Shen, C. (2018). Mask-CNN: Localizing parts and selecting descriptors for fine-grained bird species categorization. Pattern Recognition, 76, 704-714.
    DOI Scopus96 WoS66
    2018 Guo, G., Wang, H., Shen, C., Yan, Y., & Liao, H. (2018). Automatic image cropping for visual aesthetic enhancement using deep neural networks and cascaded regression. IEEE Transactions on Multimedia, 20(8), 2073-2085.
    DOI Scopus22 WoS18
    2018 You, M., Zhang, Y., Shen, C., & Zhang, X. (2018). An Extended Filtered Channel Framework for Pedestrian Detection. IEEE Transactions on Intelligent Transportation Systems, 19(5), 1640-1651.
    DOI Scopus12 WoS10
    2018 Zhang, J., Wu, Q., Shen, C., Zhang, J., & Lu, J. (2018). Multilabel image classification with regional latent semantic dependencies. IEEE Transactions on Multimedia, 20(10), 2801-2813.
    DOI Scopus63 WoS44
    2018 Zhang, L., Wei, W., Zhang, Y., Shen, C., van den Hengel, A., & Shi, Q. (2018). Cluster sparsity field: an internal hyperspectral imagery prior for reconstruction. International Journal of Computer Vision, 126(8), 797-821.
    DOI Scopus53 WoS66
    2018 Li, H., Wang, P., You, M., & Shen, C. (2018). Reading car license plates using deep neural networks. Image and Vision Computing, 72, 14-23.
    DOI Scopus61 WoS36
    2018 Lu, H., Shen, C., Cao, Z., Xiao, Y., & Van Den Hengel, A. (2018). An embarrassingly simple approach to visual domain adaptation. IEEE Transactions on Image Processing, 27(7), 3403-3417.
    DOI Scopus48 WoS44 Europe PMC2
    2018 Zhuang, N., Yan, Y., Chen, S., Wang, H., & Shen, C. (2018). Multi-label learning based deep transfer neural network for facial attribute classification. Pattern Recognition, 80, 225-240.
    DOI Scopus41 WoS30
    2018 Wu, Q., Shen, C., Wang, P., Dick, A., & van den Hengel, A. (2018). Image captioning and visual question answering based on attributes and external knowledge. IEEE Transactions on Pattern Analysis and Machine Intelligence, 40(6), 1367-1381.
    DOI Scopus139 WoS96 Europe PMC2
    2018 Cao, Y., Wu, Z., & Shen, C. (2018). Estimating Depth from Monocular Images as Classification Using Deep Fully Convolutional Residual Networks. IEEE Transactions on Circuits and Systems for Video Technology, 28(11), 3174-3182.
    DOI Scopus99 WoS124
    2018 Sheng, B., Shen, C., Lin, G., Li, J., Yang, W., & Sun, C. (2018). Crowd counting via weighted VLAD on a dense attribute feature map. IEEE Transactions on Circuits and Systems for Video Technology, 28(8), 1788-1797.
    DOI Scopus43 WoS23
    2018 Nekrasov, V., Shen, C., & Reid, I. D. (2018). Diagnostics in semantic segmentation. CoRR, abs/1809.10328, 1-16.
    2018 Cao, Y., Zhao, T., Xian, K., Shen, C., Cao, Z., & Xu, S. (2018). Monocular Depth Estimation with Augmented Ordinal Depth Relationships. IEEE Transactions on Image Processing, 1.
    DOI Scopus3
    2018 Hu, Q., Wang, P., Shen, C., Van Den Hengel, A., & Porikli, F. (2018). Pushing the limits of deep CNNs for pedestrian detection. IEEE Transactions on Circuits and Systems for Video Technology, 28(6), 1358-1368.
    DOI Scopus43 WoS37
    2017 Cao, Y., Shen, C., & Shen, H. (2017). Exploiting depth from single monocular images for object detection and semantic segmentation. IEEE Transactions on Image Processing, 26(2), 836-846.
    DOI Scopus32 WoS27 Europe PMC3
    2017 Hu, Q., Wang, H., Li, T., & Shen, C. (2017). Deep CNNs with spatially weighted pooling for fine-grained car recognition. IEEE Transactions on Intelligent Transportation Systems, 18(11), 3147-3156.
    DOI Scopus52 WoS40
    2017 Liu, L., Wang, P., Shen, C., Wang, L., Van Den Hengel, A., Wang, C., & Shen, H. (2017). Compositional model based Fisher vector coding for image classification. IEEE Transactions on Pattern Analysis and Machine Intelligence, 39(12), 2335-2348.
    DOI Scopus30 WoS18 Europe PMC2
    2017 Wu, L., Chunhua, S., & Van Den Hengel, A. (2017). Deep linear discriminant analysis on fisher networks: a hybrid architecture for person re-identification. Pattern Recognition, 65, 238-250.
    DOI Scopus131 WoS115
    2017 Wang, P., Shen, C., Van Den Hengel, A., & Torr, P. (2017). Large-scale binary quadratic optimization using semidefinite relaxation and applications. IEEE Transactions on Pattern Analysis and Machine Intelligence, 39(3), 470-485.
    DOI Scopus18 WoS19
    2017 Paisitkriangkrai, S., Wu, L., Shen, C., & van den Hengel, A. (2017). Structured learning of metric ensembles with application to person re-identification. Computer Vision and Image Understanding, 156, 51-65.
    DOI Scopus8 WoS5
    2017 Lin, G., Liu, F., Shen, C., Wu, J., & Shen, H. (2017). Structured learning of binary codes with column generation for optimizing ranking measures. International Journal of Computer Vision, 123(2), 287-308.
    DOI Scopus6 WoS5
    2017 Qiao, R., Liu, L., Shen, C., & van den Hengel, A. (2017). Learning discriminative trajectorylet detector sets for accurate skeleton-based action recognition. Pattern Recognition, 66, 202-212.
    DOI Scopus37 WoS32
    2017 Wu, Q., Teney, D., Wang, P., Shen, C., Dick, A., & van den Hengel, A. (2017). Visual question answering: a survey of methods and datasets. Computer Vision and Image Understanding, 163, 21-40.
    DOI Scopus111 WoS78
    2017 Li, Y., Liu, L., Shen, C., & Hengel, A. (2017). Mining Mid-level Visual Patterns with Deep CNN Activations. International Journal of Computer Vision, 121(3), 344-364.
    DOI Scopus24 WoS20
    2017 Wang, P., Wu, Q., Shen, C., Dick, A., & Van Den Hengel, A. (2017). FVQA: fact-based Visual Question Answering. IEEE Transactions on Pattern Analysis and Machine Intelligence, 40(10), 2413-2427.
    DOI Scopus75 WoS51 Europe PMC3
    2017 Lu, H., Cao, Z., Xiao, Y., Zhuang, B., & Shen, C. (2017). TasselNet: Counting maize tassels in the wild via local counts regression network. Plant Methods, 13(1), 17 pages.
    DOI Scopus75 WoS52 Europe PMC13
    2017 Yao, R., Shi, Q., Shen, C., Zhang, Y., & Van Den Hengel, A. (2017). Part-based robust tracking using online latent structured learning. IEEE Transactions on Circuits and Systems for Video Technology, 27(6), 1235-1248.
    DOI Scopus11 WoS10
    2017 Liu, F., Lin, G., & Shen, C. (2017). Discriminative training of deep fully connected continuous CRFs with task-specific loss. IEEE Transactions on Image Processing, 26(5), 2127-2136.
    DOI Scopus8 WoS8 Europe PMC1
    2017 Li, Y., Li, W., & Shen, C. (2017). Removal of optically thick clouds from high-resolution satellite imagery using dictionary group learning and interdictionary nonlocal joint sparse coding. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 10(5), 1870-1882.
    DOI Scopus11 WoS11
    2016 Wang, P., Cao, Y., Shen, C., Liu, L., & Shen, H. (2016). Temporal pyramid pooling based convolutional neural network for action recognition. IEEE Transactions on Circuits and Systems for Video Technology, 27(99), 1-8.
    DOI Scopus66 WoS9
    2016 Liu, F., Shen, C., Reid, I., & Van Den Hengel, A. (2016). Online unsupervised feature learning for visual tracking. Image and Vision Computing, 51, 84-94.
    DOI Scopus11 WoS10
    2016 Paisitkriangkrai, S., Shen, C., & Van Den Hengel, A. (2016). Pedestrian detection with spatially pooled features and structured ensemble learning. IEEE Transactions on Pattern Analysis and Machine Intelligence, 38(6), 1243-1257.
    DOI Scopus82 WoS66 Europe PMC5
    2016 Wang, S., Lu, J., Gu, X., Shen, C., Xia, R., & Yang, J. (2016). Canonical principal angles correlation analysis for two-view data. Journal of Visual Communication and Image Representation, 35, 209-219.
    DOI Scopus7 WoS8
    2016 Li, H., Shen, F., Shen, C., Yang, Y., & Gao, Y. (2016). Face recognition using linear representation ensembles. Pattern Recognition, 59, 72-87.
    DOI Scopus17 WoS12
    2016 Shen, F., Shen, C., Zhou, X., Yang, Y., & Shen, H. (2016). Face image classification by pooling raw features. Pattern Recognition, 54, 94-103.
    DOI Scopus43 WoS34
    2016 Liu, L., Wang, L., & Shen, C. (2016). A generalized probabilistic framework for compact codebook creation. IEEE Transactions on Pattern Analysis and Machine Intelligence, 38(2), 224-237.
    DOI Scopus3 WoS2
    2016 Hu, Q., Paisitkriangkrai, S., Shen, C., Van Den Hengel, A., & Porikli, F. (2016). Fast detection of multiple objects in traffic scenes with a common detection framework. IEEE Transactions on Intelligent Transportation Systems, 17(4), 1002-1014.
    DOI Scopus60 WoS39
    2016 Li, X., Shen, C., Dick, A., Zhang, Z., & Zhuang, Y. (2016). Online metric-weighted linear representations for robust visual tracking. IEEE Transactions on Pattern Analysis and Machine Intelligence, 38(5), 931-950.
    DOI Scopus19 WoS16
    2016 Liu, L., Shen, C., & van den Hengel, A. (2016). Cross-convolutional-layer pooling for image recognition. IEEE Transactions on Pattern Analysis and Machine Intelligence, 39(11), 2305-2313.
    DOI Scopus44 WoS37 Europe PMC5
    2016 Lin, G., Shen, C., Hengel, A., & Reid, I. (2016). Exploring context with deep structured models for semantic segmentation. IEEE Transactions on Pattern Analysis and Machine Intelligence, 40(6), 1352-1366.
    DOI Scopus43 WoS37 Europe PMC2
    2016 Zhao, X., Li, X., Zhang, Z., Shen, C., Zhuang, Y., Gao, L., & Li, X. (2016). Scalable linear visual feature learning via online parallel nonnegative matrix factorization. IEEE Transactions on Neural Networks and Learning Systems, 27(12), 2628-2642.
    DOI Scopus9 WoS9
    2016 Zhang, L., Wei, W., Zhang, Y., Shen, C., Van Den Hengel, A., & Shi, Q. (2016). Dictionary learning for promoting structured sparsity in hyperspectral compressive sensing. IEEE Transactions on Geoscience and Remote Sensing, 54(12), 7223-7235.
    DOI Scopus37 WoS32
    2016 Liu, F., Shen, C., Lin, G., & Reid, I. (2016). Learning depth from single monocular images using deep convolutional neural fields. IEEE Transactions on Pattern Analysis and Machine Intelligence, 38(10), 2024-2039.
    DOI Scopus584 WoS458 Europe PMC26
    2016 Wang, P., Shen, C., van den Hengel, A., & Torr, P. (2016). Efficient semidefinite branch-and-cut for MAP-MRF inference. International Journal of Computer Vision, 117(3), 269-289.
    DOI Scopus2 WoS1
    2016 Zhang, C., Shen, C., & Shen, T. (2016). Unsupervised Feature Learning for Dense Correspondences Across Scenes. International Journal of Computer Vision, 116(1), 90-107.
    DOI Scopus5 WoS4
    2015 Harandi, M., Hartley, R., Shen, C., Lovell, B., & Sanderson, C. (2015). Extrinsic methods for coding and dictionary learning on Grassmann manifolds. International Journal of Computer Vision, 114(2-3), 113-136.
    DOI Scopus51 WoS47
    2015 Luo, L., Shen, C., Liu, X., & Zhang, C. (2015). A computational model of the short-cut rule for 2D shape decomposition. IEEE Transactions on Image Processing, 24(1), 273-283.
    DOI Scopus14 WoS15
    2015 Li, H., Shen, C., Van Den Hengel, A., & Shi, Q. (2015). Worst case linear discriminant analysis as scalable semidefinite feasibility problems. IEEE Transactions on Image Processing, 24(8), 2382-2392.
    DOI Scopus6 WoS5
    2015 Lin, G., Shen, C., & van den Hengel, A. (2015). Supervised hashing using graph cuts and boosted decision trees. IEEE Transactions on Pattern Analysis and Machine Intelligence, 37(11), 2317-2331.
    DOI Scopus64 WoS54 Europe PMC6
    2015 Shen, F., Shen, C., Shi, Q., Van Den Hengel, A., Tang, Z., & Shen, H. (2015). Hashing on nonlinear manifolds. IEEE Transactions on Image Processing, 24(6), 1839-1851.
    DOI Scopus123 WoS106 Europe PMC13
    2015 Liu, F., Lin, G., & Shen, C. (2015). CRF learning with CNN features for image segmentation. Pattern Recognition, 48(10), 2983-2992.
    DOI Scopus140 WoS114
    2014 Shen, C., Lin, G., & van den Hengel, A. (2014). StructBoost: boosting methods for predicting structured output variables. IEEE Transactions on Pattern Analysis and Machine Intelligence, 36(10), 2089-2103.
    DOI Scopus11 WoS6 Europe PMC2
    2014 Wang, L., Zhou, L., Shen, C., Liu, L., & Liu, H. (2014). A hierarchical word-merging algorithm with class separability measure. IEEE Transactions on Pattern Analysis and Machine Intelligence, 36(3), 417-435.
    DOI Scopus13 WoS9 Europe PMC1
    2014 Paisitkriangkrai, S., Shen, C., & Van Den Hengel, A. (2014). Large-margin learning of compact binary image encodings. IEEE Transactions on Image Processing, 23(9), 4041-4054.
    DOI Scopus1 WoS1 Europe PMC1
    2014 Shen, C., Kim, J., Liu, F., Wang, L., & van den Hengel, A. (2014). Efficient dual approach to distance metric learning. IEEE Transactions on Neural Networks and Learning Systems, 25(2), 394-406.
    DOI Scopus28 WoS24 Europe PMC6
    2014 Lu, Y., Wang, L., Lu, J., Yang, J., & Shen, C. (2014). Multiple kernel clustering based on centered kernel alignment. Pattern Recognition, 47(11), 3656-3664.
    DOI Scopus62 WoS45
    2014 Paisitkriangkrai, S., Shen, C., & van den Hengel, A. (2014). Asymmetric pruning for learning cascade detectors. IEEE Transactions on Multimedia, 16(5), 1254-1267.
    DOI Scopus4 WoS2
    2014 Yan, Y., Wang, H., & Shen, C. (2014). Efficient semidefinite spectral clustering via lagrange duality. IEEE Transactions on Image Processing, 23(8), 3522-3534.
    DOI Scopus9 WoS8
    2014 Liu, F., Zhou, L., Shen, C., & Yin, J. (2014). Multiple kernel learning in the primal for multimodal Alzheimer's disease classification. IEEE Journal of Biomedical and Health Informatics, 18(3), 984-990.
    DOI Scopus79 WoS61 Europe PMC28
    2014 Paisitkriangkrai, S., Shen, C., Shi, Q., & van den Hengel, A. (2014). RandomBoost: simplified multiclass boosting through randomization. IEEE Transactions on Neural Networks and Learning Systems, 25(4), 764-779.
    DOI Scopus6 WoS7 Europe PMC1
    2014 Li, Y., Jia, W., Shen, C., & van den Hengel, A. (2014). Characterness: an indicator of text in the wild. IEEE Transactions on Image Processing, 23(4), 1666-1677.
    DOI Scopus71 WoS61 Europe PMC5
    2014 Shen, F., Shen, C., Hill, R., Van Den Hengel, A., & Tang, Z. (2014). Fast approximate L∞ minimization: speeding up robust regression. Computational Statistics & Data Analysis, 77, 25-37.
    DOI Scopus12 WoS12
    2014 Paisitkriangkrai, S., Shen, C., & Van Den Hengel, A. (2014). A scalable stagewise approach to large-margin multiclass loss-based boosting. IEEE Transactions on Neural Networks and Learning Systems, 25(5), 1002-1013.
    DOI Scopus8 WoS9 Europe PMC2
    2013 Li, X., Dick, A., Shen, C., Van Den Hengel, A., & Wang, H. (2013). Incremental learning of 3D-DCT compact representations for robust visual tracking. IEEE Transactions on Pattern Analysis and Machine Intelligence, 35(4), 863-881.
    DOI Scopus77 WoS63 Europe PMC6
    2013 Luo, L., Shen, C., Zhang, C., & Van Den Hengel, A. (2013). Shape similarity analysis by self-tuning locally constrained mixed-diffusion. IEEE Transactions on Multimedia, 15(5), 1174-1183.
    DOI Scopus22 WoS20
    2013 Shen, C., Li, H., & Van Den Hengel, A. (2013). Fully corrective boosting with arbitrary loss and regularization. Neural Networks, 48, 44-58.
    DOI Scopus7 WoS6 Europe PMC2
    2013 Li, X., Dick, A., Shen, C., Zhang, Z., Van Den Hengel, A., & Wang, H. (2013). Visual tracking with spatio-temporal Dempster-Shafer information fusion. IEEE Transactions on Image Processing, 22(8), 3028-3040.
    DOI Scopus30 WoS29 Europe PMC5
    2013 Shen, F., Shen, C., Van Den Hengel, A., & Tang, Z. (2013). Approximate least trimmed sum of squares fitting and applications in image analysis. IEEE Transactions on Image Processing, 22(5), 1836-1847.
    DOI Scopus26 WoS20
    2013 Li, X., Hu, W., Shen, C., Dick, A., & Zhang, Z. (2013). Context-aware hypergraph construction for robust spectral clustering. IEEE Transactions on Knowledge & Data Engineering, 26(10), 1-9.
    DOI Scopus32 WoS31
    2013 Li, X., Hu, W., Shen, C., Zhang, Z., Dick, A., & Van Den Hengel, A. (2013). A survey of appearance models in visual object tracking. ACM Transactions on Intelligent Systems and Technology, 4(58), 1-48.
    DOI Scopus575 WoS525
    2013 Shen, C., Wang, P., Paisitkriangkrai, S., & Van Den Hengel, A. (2013). Training effective node classifiers for cascade classification. International Journal of Computer Vision, 103(3), 326-347.
    DOI Scopus26 WoS22
    2012 Shen, C., Kim, J., Wang, L., & Van Den Hengel, A. (2012). Positive semidefinite metric learning using boosting-like algorithms. Journal of Machine Learning Research (Print), 13(0), 1007-1036.
    Scopus67 WoS54
    2012 Wang, P., Shen, C., Barnes, N., & Zheng, H. (2012). Fast and robust object detection using asymmetric totally-corrective boosting. IEEE Transactions on Neural Networks and Learning Systems, 23(1), 33-46.
    DOI Scopus30 WoS27 Europe PMC12
    2012 Shen, C., Wang, P., Shen, F., & Wang, H. (2012). UBoost: Boosting with the Universum. IEEE Transactions on Pattern Analysis and Machine Intelligence, 34(4), 825-832.
    DOI Scopus38 WoS34 Europe PMC1
    2011 Shen, C., Paisitkriangkrai, S., & Zhang, J. (2011). Efficiently learning a detection cascade with sparse eigenvectors. IEEE Transactions on Image Processing, 20(1), 22-35.
    DOI Scopus26 WoS21 Europe PMC3
    2011 Paisitkriangkrai, S., Shen, C., & Zhang, J. (2011). Incremental training of a detector using online sparse eigendecomposition. IEEE Transactions on Image Processing, 20(1), 213-226.
    DOI Scopus13 WoS9 Europe PMC2
    2010 Shen, C., Kim, J., & Wang, H. (2010). Generalized kernel-based visual tracking. IEEE Transactions on Circuits and Systems for Video Technology, 20(1), 119-130.
    DOI Scopus81 WoS64
    2010 Shen, C. (2010). On the dual formulation of boosting algorithms. IEEE Transactions on Pattern Analysis and Machine Intelligence, 32(12), 2216-2231.
    DOI Scopus70
    2010 Shen, C., & Li, H. (2010). Boosting through optimization of margin distributions. IEEE Transactions on Neural Networks, 21(4), 659-666.
    DOI Scopus51 Europe PMC11
    2010 Shen, C., Kim, J., & Wang, L. (2010). Scalable large-margin Mahalanobis distance metric learning. IEEE Transactions on Neural Networks, 21(9), 1524-1530.
    DOI Scopus52 Europe PMC10
    2010 Zhou, L., Wang, L., & Shen, C. (2010). Feature selection with redundancy-constrained class separability. IEEE Transactions on Neural Networks, 21(5), 853-858.
    DOI Scopus48 Europe PMC8
    2010 Li, H., & Shen, C. (2010). Interactive color image segmentation with linear programming. Machine Vision and Applications, 21(4), 403-412.
    DOI Scopus11
    2008 Paisitkriangkrai, S., Shen, C., & Zhang, J. (2008). Performance evaluation of local features in human classification and detection. IET Computer Vision, 2(4), 236-246.
    DOI Scopus39 WoS32
    2008 Paisitkriangkrai, S., Shen, C., & Zhang, J. (2008). Fast pedestrian detection using a cascade of boosted covariance features. IEEE Transactions on Circuits and Systems for Video Technology, 18(8), 1140-1151.
    DOI Scopus112
    2008 Shen, C., Li, H., & Brooks, M. (2008). Supervised dimensionality reduction via sequential semidefinite programming. Pattern Recognition, 41(12), 3644-3652.
    DOI Scopus23 WoS22
    2007 Wang, H., Suter, D., Schindler, K., & Shen, C. (2007). Adaptive object tracking based on an effective appearance filter. IEEE Transactions on Pattern Analysis and Machine Intelligence, 29(9), 1661-1667.
    DOI Scopus180 WoS124 Europe PMC15
    2007 Shen, C., Brooks, M., & Van Den Hengel, A. (2007). Fast global kernel density mode seeking: Applications to localization and tracking. IEEE Transactions on Image Processing, 16(5), 1457-1469.
    DOI Scopus70 WoS51 Europe PMC5
    2004 Lin, Z., Lu, J., Shen, C., Qiu, X., & Xu, B. (2004). Active control of radiation from a piston set in a rigid sphere. Journal of the Acoustical Society of America, 115(6), 2954-2963.
    DOI Scopus16 Europe PMC2
    2003 Lu, J., Shen, C., Qiu, X., & Xu, B. (2003). Lattice form adaptive infinite impulse response filtering algorithm for active noise control. Journal of the Acoustical Society of America, 113(1), 327-335.
    DOI Scopus22 Europe PMC2
    — Liu, Y., Chen, H., Chen, Y., Yin, W., & Shen, C. (n.d.). Generic Perceptual Loss for Modeling Structured Output Dependencies.
    — Mao, W., Ge, Y., Shen, C., Tian, Z., Wang, X., & Wang, Z. (n.d.). TFPose: Direct Human Pose Estimation with Transformers.
    — Yuan, J., Liu, Y., Shen, C., Wang, Z., & Li, H. (n.d.). A Simple Baseline for Semi-supervised Semantic Segmentation with Strong
    Data Augmentation.
    — Zhou, Q., Yu, C., Shen, C., Wang, Z., & Li, H. (n.d.). Object Detection Made Simpler by Eliminating Heuristic NMS.
    — Tian, Z., Zhang, B., Chen, H., & Shen, C. (n.d.). Instance and Panoptic Segmentation Using Conditional Convolutions.
    — Yin, W., Zhang, J., Wang, O., Niklaus, S., Mai, L., Chen, S., & Shen, C. (n.d.). Learning to Recover 3D Scene Shape from a Single Image.
    — He, T., Shen, C., & Hengel, A. V. D. (n.d.). Dynamic Convolution for 3D Point Cloud Instance Segmentation.
    — Zhang, B., Liu, Y., Tian, Z., & Shen, C. (n.d.). Dynamic Neural Representational Decoders for High-Resolution Semantic
    Segmentation.
    — Mao, W., Tian, Z., Wang, X., & Shen, C. (n.d.). FCPose: Fully Convolutional Multi-Person Pose Estimation with Dynamic
    Instance-Aware Convolutions.
    — Tian, Z., Shen, C., Wang, X., & Chen, H. (n.d.). BoxInst: High-Performance Instance Segmentation with Box Annotations.
    — Wang, X., Zhang, R., Shen, C., Kong, T., & Li, L. (n.d.). Dense Contrastive Learning for Self-Supervised Visual Pre-Training.
    — He, T., Shen, C., & Hengel, A. V. D. (n.d.). DyCo3D: Robust Instance Segmentation of 3D Point Clouds through Dynamic
    Convolution.
    — Wang, H., Chen, P., Zhuang, B., & Shen, C. (n.d.). Fully Quantized Image Super-Resolution Networks.
    — Dai, Y., Lu, H., & Shen, C. (n.d.). Learning Affinity-Aware Upsampling for Deep Image Matting.
    — Wang, Y., Xu, Z., Wang, X., Shen, C., Cheng, B., Shen, H., & Xia, H. (n.d.). End-to-End Video Instance Segmentation with Transformers.
    — Chen, H., Shen, C., & Tian, Z. (n.d.). Unifying Instance and Panoptic Segmentation with Dynamic Rank-1
    Convolutions.
    — Zhang, J., Xie, Y., Xia, Y., & Shen, C. (n.d.). DoDNet: Learning to segment multi-organ and tumors from multiple
    partially labeled datasets.
    — Shu, C., Liu, Y., Gao, J., Yan, Z., & Shen, C. (n.d.). Channel-wise Knowledge Distillation for Dense Prediction.
    — Tian, Z., Shen, C., Chen, H., & He, T. (n.d.). FCOS: A simple and strong anchor-free object detector.
    — Zhuang, B., Liu, L., Shen, C., & Reid, I. (n.d.). Towards Context-aware Interaction Recognition.
    — Zhuang, B., Shen, C., & Reid, I. (n.d.). Training Compact Neural Networks with Binary Weights and Low Precision
    Activations.
    — Wu, Z., Shen, C., & Hengel, A. V. D. (n.d.). Real-time Semantic Image Segmentation via Spatial Sparsity.
    — Deng, R., Zhao, T., Shen, C., & Liu, S. (n.d.). Relative Depth Order Estimation Using Multi-scale Densely Connected
    Convolutional Networks.
    — Zhuang, B., Wu, Q., Shen, C., Reid, I., & Hengel, A. V. D. (n.d.). Care about you: towards large-scale human-centric visual relationship
    detection.
    — Qiao, R., Liu, L., Shen, C., & Hengel, A. V. D. (n.d.). Visually Aligned Word Embeddings for Improving Zero-shot Learning.
    — Liu, W., Chen, X., Shen, C., Yu, J., Wu, Q., & Yang, J. (n.d.). Robust Guided Image Filtering.
    — Wang, P., Liu, L., Shen, C., Hengel, A. V. D., & Shen, H. T. (n.d.). Hi Detector, What's Wrong with that Object? Identifying Irregular Object
    From Images by Modelling the Detection Score Distribution.
    — Lin, G., Liu, F., Shen, C., Wu, J., & Shen, H. T. (n.d.). Structured Learning of Binary Codes with Column Generation.
    — Liu, F., & Shen, C. (n.d.). Learning Deep Convolutional Features for MRI Based Alzheimer's Disease
    Classification.
    — Shen, C., & Liu, F. (n.d.). From Kernel Machines to Ensemble Learning.
    — Shen, F., & Shen, C. (n.d.). Generic Image Classification Approaches Excel on Face Recognition.
    — Shen, C., Paisitkriangkrai, S., & Hengel, A. V. D. (n.d.). A Direct Approach to Multi-class Boosting and Extensions.
    — Shen, C., Li, H., & Barnes, N. (n.d.). Totally Corrective Boosting for Regularized Risk Minimization.
    — Zheng, Y., Shen, C., Hartley, R., & Huang, X. (n.d.). Effective Pedestrian Detection Using Center-symmetric Local
    Binary/Trinary Patterns.
    — Hao, Z., Shen, C., Barnes, N., & Wang, B. (n.d.). Totally Corrective Multiclass Boosting with Binary Weak Learners.
    — Li, H., Shen, C., & Shi, Q. (n.d.). Real-time Visual Tracking Using Sparse Representation.
    — Shen, C., Wang, P., & Hengel, A. V. D. (n.d.). Optimally Training a Cascade Classifier.
    — Wu, L., Shen, C., & Hengel, A. V. D. (n.d.). PersonNet: Person Re-identification with Deep Convolutional Neural
    Networks.
    — Mao, X. -J., Shen, C., & Yang, Y. -B. (n.d.). Image Restoration Using Convolutional Auto-encoders with Symmetric Skip
    Connections.
    — Wu, L., Shen, C., & Hengel, A. V. D. (n.d.). Deep Recurrent Convolutional Networks for Video-based Person
    Re-identification: An End-to-End Approach.
    — Wu, Z., Shen, C., & Hengel, A. V. D. (n.d.). Bridging Category-level and Instance-level Semantic Image Segmentation.
    — Wu, Z., Shen, C., & Hengel, A. V. D. (n.d.). High-performance Semantic Segmentation Using Very Deep Fully
    Convolutional Networks.
    — Li, H., & Shen, C. (n.d.). Reading Car License Plates Using Deep Convolutional Neural Networks and
    LSTMs.
    — Wang, X., Man, Z., You, M., & Shen, C. (n.d.). Adversarial Generation of Training Examples: Applications to Moving
    Vehicle License Plate Recognition.
    — Xiong, H., Lu, H., Liu, C., Liu, L., Shen, C., & Cao, Z. (n.d.). From Open Set to Closed Set: Supervised Spatial Divide-and-Conquer for
    Object Counting.
    — Cao, J., Liu, L., Wang, P., Huang, Z., Shen, C., & Shen, H. T. (n.d.). Where to Focus: Query Adaptive Matching for Instance Retrieval Using
    Convolutional Feature Maps.
    — Tian, Z., Chen, H., & Shen, C. (n.d.). DirectPose: Direct End-to-End Multi-Person Pose Estimation.
    — Yin, W., Wang, X., Shen, C., Liu, Y., Tian, Z., Xu, S., . . . Renyin, D. (n.d.). DiverseDepth: Affine-invariant Depth Prediction Using Diverse Data.
    — Lu, H., Dai, Y., Shen, C., & Xu, S. (n.d.). Index Network.
    — Zhuang, B., Shen, C., Tan, M., Chen, P., Liu, L., & Reid, I. (n.d.). Structured Binary Neural Networks for Image Recognition.
    — Wang, P., Li, H., & Shen, C. (n.d.). Towards End-to-End Text Spotting in Natural Scenes.
    — Zhang, H., Li, Y., Wang, P., Liu, Y., & Shen, C. (n.d.). RGB-D Based Action Recognition with Light-weight 3D Convolutional
    Networks.

  • Conference Papers
    Year Citation
    2021 Pang, G., Van Den Hengel, A., Shen, C., & Cao, L. (2021). Toward Deep Supervised Anomaly Detection: Reinforcement Learning from Partially Labeled Anomaly Data. In Proceedings of the ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (pp. 1298-1308). ACM.
    DOI
    2020 Wang, H., Pang, G., Shen, C., & Ma, C. (2020). Unsupervised representation learning by predicting random distances. In IJCAI International Joint Conference on Artificial Intelligence Vol. 2021-January (pp. 2950-2956). online: AAAI Press.
    Scopus6
    2020 Xie, E., Wang, W., Wang, W., Ding, M., Shen, C., & Luo, P. (2020). Segmenting Transparent Objects in the Wild. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) Vol. 12358 LNCS (pp. 696-711). Switzerland: Springer International Publishing.
    DOI
    2020 Wang, W., Xie, E., Liu, X., Wang, W., Liang, D., Shen, C., & Bai, X. (2020). Scene Text Image Super-Resolution in the Wild. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) Vol. 12355 LNCS (pp. 650-666). Switzerland: Springer International Publishing.
    DOI Scopus3
    2020 He, T., Gong, D., Tian, Z., & Shen, C. (2020). Learning and Memorizing Representative Prototypes for 3D Point Cloud Semantic and Instance Segmentation. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) Vol. 12363 LNCS (pp. 564-580). Switzerland: Springer International Publishing.
    DOI Scopus1
    2020 Teney, D., Wang, P., Cao, J., Liu, L., Shen, C., & Van Den Hengel, A. (2020). V-PROM: A benchmark for visual reasoning using visual progressive matrices. In Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence (AAAI-20) Vol. 34 (pp. 12071-12078). Palo Alto, CA: Association for the Advancement of Artificial Intelligence.
    DOI Scopus1
    2020 Xie, Y., Zhang, J., Liao, Z., Verjans, J., Shen, C., & Xia, Y. (2020). Pairwise Relation Learning for Semi-supervised Gland Segmentation.. In A. L. Martel, P. Abolmaesumi, D. Stoyanov, D. Mateus, M. A. Zuluaga, S. K. Zhou, . . . L. Joskowicz (Eds.), MICCAI (5) Vol. 12265 (pp. 417-427). Switzerland: Springer Nature.
    DOI Scopus1
    2020 Nekrasov, V., Chen, H., Shen, C., & Reid, I. D. (2020). Architecture search of dynamic cells for semantic video segmentation. In Proceedings of the IEEE Winter Conference on Applications of Computer Vision (WACV '20) (pp. 1959-1968). online: IEEE.
    DOI Scopus2 WoS1
    2020 Liao, Z., Liu, L., Wu, Q., Teney, D., Shen, C., Van Den Hengel, A., & Verjans, J. (2020). Medical data inquiry using a question answering model. In Proceedings: 2020 IEEE 17th International Symposium on Biomedical Imaging (ISBI 2020) Vol. 2020-April (pp. 1490-1493). online: IEEE.
    DOI Scopus2
    2020 He, T., Liu, Y., Shen, C., Wang, X., & Sun, C. (2020). Instance-Aware Embedding for Point Cloud Instance Segmentation. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) Vol. 12375 LNCS (pp. 255-270). Switzerland: Springer Nature.
    DOI Scopus1
    2020 Qi, Y., Wu, Q., Anderson, P., Wang, X., Wang, W. Y., Shen, C., & Van Den Hengel, A. (2020). Reverie: Remote embodied visual referring expression in real indoor environments. In Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition (pp. 9979-9988). online: IEEE.
    DOI Scopus13
    2020 Xie, E., Sun, P., Song, X., Wang, W., Liu, X., Liang, D., . . . Luo, P. (2020). PolarMask: Single shot instance segmentation with polar representation. In Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition (pp. 12190-12199). online: IEEE.
    DOI Scopus40
    2020 Zhang, C., Cai, Y., Lin, G., & Shen, C. (2020). DeepEMD: Few-shot image classification with differentiable earth mover's distance and structured classifiers. In Proceedings of the 2020 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (pp. 12200-12210). online: IEEE.
    DOI Scopus20
    2020 Liao, Z., Wu, Q., Shen, C., Van Den Hengel, A., & Verjans, J. (2020). AIML at VQA-Med 2020: Knowledge inference via a skeleton-based sentence mapping approach for medical domain visual question answering. In L. Cappellato, C. Eickhoff, N. Ferro, & A. Névéol (Eds.), Proceedings of the 11th International Conference of the CLEF Initiative (CLEF 2020), as published in CEUR Workshop Proceedings Vol. 2696 (pp. 1-14). online: CEUR-WS.
    2020 Yu, C., Liu, Y., Gao, C., Shen, C., & Sang, N. (2020). Representative Graph Neural Network. In Proceedings of the 16th European Conference on Computer Vision (ECCV) Vol. VII (pp. 379-396). Switzerland: Springer Nature.
    DOI Scopus5
    2020 Wang, N., Gao, Y., Chen, H., Wang, P., Tian, Z., Shen, C., & Zhang, Y. (2020). NAS-FCOS: Fast Neural Architecture Search for Object Detection. In Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition (pp. 11940-11948). online: IEEE.
    DOI Scopus12
    2020 Wang, H., Wu, Q., & Shen, C. (2020). Soft Expert Reward Learning for Vision-and-Language Navigation. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) Vol. 12354 LNCS (pp. 126-141). Switzerland: Springer Nature.
    DOI
    2020 Wang, W., Liu, X., Ji, X., Xie, E., Liang, D., Yang, Z. B., . . . Luo, P. (2020). AE TextSpotter: Learning visual and linguistic representation for ambiguous text spotting. In Proceedings of the 16th European Conference on Computer Vision (ECCV 2020), as published in Lecture Notes in Computer Science Vol. 12359 (pp. 457-473). Cham, Switzerland: Springer.
    DOI
    2020 Nekrasov, V., Shen, C., & Reid, I. D. (2020). Template-based automatic search of compact semantic segmentation architectures. In Proceedings of the IEEE Winter Conferene on Applications of Computer Vision (WACV 2020) Vol. abs/1904.02365 (pp. 1969-1978). online: IEEE.
    DOI Scopus2
    2020 Chen, H., Sun, K., Tian, Z., Shen, C., Huang, Y., & Yan, Y. (2020). Blendmask: Top-down meets bottom-up for instance segmentation. In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR 2020) (pp. 8570-8578). online: IEEE.
    DOI Scopus44
    2020 Wang, X., Liu, Y., Shen, C., Ng, C. C., Luo, C., Jin, L., . . . Wang, L. (2020). On the general value of evidence, and bilingual scene-text visual question answering. In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR 2020) (pp. 10123-10132). online: IEEE.
    DOI Scopus3
    2020 Liu, Y., Shen, C., Yu, C., & Wang, J. (2020). Efficient Semantic Video Segmentation with Per-Frame Inference. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) Vol. 12355 LNCS (pp. 352-368). Switzerland: Springer International Publishing.
    DOI Scopus2
    2020 Liu, Y., Chen, H., Shen, C., He, T., Jin, L., & Wang, L. (2020). ABCNet: Real-time scene text spotting with adaptive Bezier-curve network. In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR 2020) (pp. 9806-9815). online: IEEE.
    DOI Scopus21
    2020 Tian, Z., Shen, C., & Chen, H. (2020). Conditional Convolutions for Instance Segmentation. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) Vol. 12346 LNCS (pp. 282-298). Switzerland: Springer International Publishing.
    DOI Scopus4
    2020 Pang, G., Yan, C., Shen, C., van den Hengel, A., & Bai, X. (2020). Self-trained deep ordinal regression for end-to-end video anomaly detection. In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR 2020) (pp. 12170-12179). online: IEEE.
    DOI Scopus17
    2020 Yu, C., Wang, J., Gao, C., Yu, G., Shen, C., & Sang, N. (2020). Context prior for scene segmentation. In Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition (pp. 12413-12422). online: IEEE.
    DOI Scopus19
    2020 Zhang, R., Tian, Z., Shen, C., You, M., & Yan, Y. (2020). Mask Encoding for Single Shot Instance Segmentation. In Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition (pp. 10223-10232). online: IEEE.
    DOI Scopus7
    2019 Wang, W., Xie, E., Song, X., Zang, Y., Wang, W., Lu, T., . . . Shen, C. (2019). Efficient and accurate arbitrary-shaped text detection with pixel aggregation network. In Proceedings of the IEEE International Conference on Computer Vision (ICCV) Vol. 2019-October (pp. 8439-8448). online: IEEE.
    DOI Scopus45 WoS6
    2019 Xiong, H., Lu, H., Liu, C., Liu, L., Cao, Z., & Shen, C. (2019). From open set to closed set: Counting objects by spatial divide-and-conquer. In Proceedings of the IEEE International Conference on Computer Vision Vol. 2019-October (pp. 8361-8370). online: IEEE.
    DOI Scopus41 WoS26
    2019 Yan, Q., Gong, D., Shi, Q., Van Den Hengel, A., Shen, C., Reid, I., & Zhang, Y. (2019). Attention-guided network for ghost-free high dynamic range imaging. In Proceedings: 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition Vol. 2019-June (pp. 1751-1760). online: IEEE.
    DOI Scopus34 WoS19
    2019 Zhang, J., Wu, Q., Zhang, J., Shen, C., & Lu, J. (2019). Mind your neighbours: Image annotation with metadata neighbourhood graph co-attention networks. In Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition Vol. 2019-June (pp. 2951-2959). online: IEEE.
    DOI Scopus8 WoS2
    2019 Wang, P., Wu, Q., Cao, J., Shen, C., Gao, L., & Hengel, A. (2019). Neighbourhood watch: Referring expression comprehension via language-guided graph attention networks. In Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition Vol. 2019-June (pp. 1960-1968). online: IEEE.
    DOI Scopus46 WoS9
    2019 Zhang, C., Lin, G., Liu, F., Yao, R., & Shen, C. (2019). CANET: Class-agnostic segmentation networks with iterative refinement and attentive few-shot learning. In Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition Vol. 2019-June (pp. 5212-5221). online: IEEE.
    DOI Scopus51 WoS13
    2019 Bian, J. -W., Li, Z., Wang, N., Zhan, H., Shen, C., Cheng, M. -M., & Reid, I. (2019). Unsupervised Scale-consistent Depth and Ego-motion Learning from Monocular Video. In H. Wallach, H. Larochelle, A. Beygelzimer, F. d'Alche-Buc, E. Fox, & R. Garnett (Eds.), ADVANCES IN NEURAL INFORMATION PROCESSING SYSTEMS 32 (NIPS 2019) Vol. 32 (pp. 1-12). online: NIPS Proceedings.
    Scopus46 WoS13
    2019 Yan, C., Pang, G., Bai, X., Shen, C., Zhou, J., & Hancock, E. (2019). Deep hashing by discriminating hard examples. In MM 2019 - Proceedings of the 27th ACM International Conference on Multimedia (pp. 1535-1542). online: ACM.
    DOI Scopus5 WoS1
    2019 Zhang, J., Xie, Y., Zhang, P., Chen, H., Xia, Y., & Shen, C. (2019). Light-weight hybrid convolutional network for liver tumor segmentation. In IJCAI International Joint Conference on Artificial Intelligence Vol. 2019-August (pp. 4271-4277). online: AAAI Press.
    DOI Scopus25
    2019 Xie, Y., Lu, H., Zhang, J., Shen, C., & Xia, Y. (2019). Deep segmentation-emendation model for gland instance segmentation. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) Vol. 11764 LNCS (pp. 469-477). Switzerland: Springer.
    DOI Scopus10 WoS1
    2019 Wang, X., Liu, S., Shen, X., Shen, C., & Jia, J. (2019). Associatively segmenting instances and semantics in point clouds. In Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition Vol. 2019-June (pp. 4091-4100). online: IEEE.
    DOI Scopus50 WoS24
    2019 He, T., Shen, C., Tian, Z., Gong, D., Sun, C., & Yan, Y. (2019). Knowledge adaptation for efficient semantic segmentation. In Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition Vol. 2019-June (pp. 578-587). online: IEEE.
    DOI Scopus45 WoS28
    2019 Tian, Z., He, T., Shen, C., & Yan, Y. (2019). Decoders matter for semantic segmentation: Data-dependent decoding enables flexible feature aggregation. In Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition Vol. 2019-June (pp. 3121-3130). online: IEEE.
    DOI Scopus72 WoS57
    2019 Li, H., Wang, P., Shen, C., & Van Den Hengel, A. (2019). Visual question answering as reading comprehension. In Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition Vol. 2019-June (pp. 6312-6321). online: IEEE.
    DOI Scopus19 WoS11
    2019 Zhuang, B., Shen, C., Tan, M., Liu, L., & Reid, I. (2019). Structured binary neural networks for accurate image classification and semantic segmentation. In Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition Vol. 2019-June (pp. 413-422). online: IEEE.
    DOI Scopus35 WoS16
    2019 Wei, X. S., Zhang, C. L., Liu, L., Shen, C., & Wu, J. (2019). Coarse-to-fine: A RNN-based hierarchical attention model for vehicle re-identification. In Proceedings of the 14th Asian Conference on Computer Vision (ACCV 2018), as published in Lecture Notes in Computer Science Vol. 11362 (pp. 575-591). Switzerland: Springer.
    DOI Scopus7 WoS7
    2019 Yin, W., Liu, Y., Shen, C., & Yan, Y. (2019). Enforcing geometric constraints of virtual normal for depth prediction. In Proceedings of the IEEE/CVF International Conference on Computer Vision (ICCV 2019) Vol. 2019-October (pp. 5683-5692). Piscataway, NJ: IEEE.
    DOI Scopus63 WoS39
    2019 Zhang, X., Cao, J., Shen, C., & You, M. (2019). Self-training with progressive augmentation for unsupervised cross-domain person re-identification. In Proceedings of the IEEE International Conference on Computer Vision Vol. 2019-October (pp. 8221-8230). online: IEEE.
    DOI Scopus55 WoS42
    2019 Zhang, H., Shen, C., Li, Y., Cao, Y., Liu, Y., & Yan, Y. (2019). Exploiting temporal consistency for real-time video depth estimation. In Proceedings of the IEEE International Conference on Computer Vision (ICCV) Vol. 2019-October (pp. 1725-1734). online: IEEE.
    DOI Scopus18 WoS17
    2019 Lu, H., Dai, Y., Shen, C., & Xu, S. (2019). Indices matter: Learning to index for deep image matting. In Proceedings of the IEEE/CVF International Conference on Computer Vision Vol. 2019-October (pp. 3265-3274). Seoul, South Korea: IEEE.
    DOI Scopus20 WoS17
    2019 Pang, G., Shen, C., & Van Den Hengel, A. (2019). Deep anomaly detection with deviation networks. In KDD '19: Proceedings of the 25th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining (pp. 353-362). New York: Association of Computing Machinery.
    DOI Scopus40 WoS11
    2019 Cai, M., Shen, C., & Reid, I. (2019). A hybrid probabilistic model for camera relocalization. In Proceedings of the 29th British Machine Vision Conference (BMVC 2018) (pp. 1-12). Newcastle upon Tyne, UK: BMVC Press.
    Scopus2
    2019 Tian, Z., Shen, C., Chen, H., & He, T. (2019). FCOS: Fully convolutional one-stage object detection. In Proceedings of the IEEE International Conference on Computer Vision Vol. 2019-October (pp. 9626-9635). online: IEEE.
    DOI Scopus500 WoS379
    2019 Nekrasov, V., Dharmasiri, T., Spek, A., Drummond, T., Shen, C., & Reid, I. (2019). Real-time joint semantic segmentation and depth estimation using asymmetric annotations. In Proceedings of the 2019 IEEE International Conference on Robotics and Automation (ICRA) Vol. 2019-May (pp. 7101-7107). Montreal, Canada: IEEE.
    DOI Scopus22 WoS13
    2019 Nekrasov, V., Chen, H., Shen, C., & Reid, I. D. (2019). Fast neural architecture search of compact semantic segmentation models via auxiliary cells. In Proceedings: 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR 2019) Vol. 2019-June (pp. 9126-9135). online: Computer Vision Foundation / IEEE.
    DOI Scopus32 WoS13
    2019 Li, H., Wang, P., Shen, C., & Zhang, G. (2019). Show, Attend and Read: A Simple and Strong Baseline for Irregular Text Recognition. In THIRTY-THIRD AAAI CONFERENCE ON ARTIFICIAL INTELLIGENCE / THIRTY-FIRST INNOVATIVE APPLICATIONS OF ARTIFICIAL INTELLIGENCE CONFERENCE / NINTH AAAI SYMPOSIUM ON EDUCATIONAL ADVANCES IN ARTIFICIAL INTELLIGENCE (pp. 8610-8617). online: AAAI.
    Scopus62 WoS21
    2019 Li, R., Xian, K., Shen, C., Cao, Z., Lu, H., & Hang, L. (2019). Deep attention-based classification network for robust depth prediction. In Proceedings of the 14th Asian Conference on Computer Vision (ACCV 2018), as published in Lecture Notes in Computer Science Vol. 11364 (pp. 663-678). Cham, Switzerland: Springer.
    DOI Scopus13 WoS3
    2019 Cao, J., Mo, L., Zhang, Y., Jia, K., Shen, C., & Tan, M. (2019). Multi-marginal wasserstein GAN. In H. Wallach, H. Larochelle, A. Beygelzimer, F. d'Alche-Buc, E. Fox, & R. Garnett (Eds.), Advances in Neural Information Processing Systems Vol. 32 (pp. 1-11). online: Neural Information Processing Systems (NIPS).
    Scopus16 WoS5
    2018 Cao, I., Guo, Y., Wu, Q., Shen, C., Huang, J., & Tan, M. (2018). Adversarial learning with local coordinate coding. In 35th International Conference on Machine Learning, ICML 2018 Vol. 2 (pp. 1104-1117). online: PMLR.
    Scopus12 WoS12
    2018 He, T., Tian, Z., Huang, W., Shen, C., Qiao, Y., & Sun, C. (2018). An end-to-end textspotter with explicit alignment and attention. In Proceedings: 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR 2018)) (pp. 5020-5029). Salt Lake City, UT: IEEE.
    DOI Scopus90 WoS54
    2018 Zhuang, B., Shen, C., Tan, M., Liu, L., & Reid, I. (2018). Towards effective low-bitwidth convolutional neural networks. In Proceedings of the 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR 2018) (pp. 7920-7928). Piscataway, NJ.: IEEE.
    DOI Scopus66 WoS34
    2018 Zhuang, B., Wu, Q., Shen, C., Reid, I., & van den Hengel, A. (2018). Parallel attention: a unified framework for visual object discovery through dialogs and queries. In Proceedings: 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR 2018) (pp. 4252-4261). Salt Lake City, UT: IEEE.
    DOI Scopus30 WoS7
    2018 Zhang, P., Liu, W., Lu, H., & Shen, C. (2018). Salient object detection by lossless feature reflection. In IJCAI International Joint Conference on Artificial Intelligence Vol. 2018-July (pp. 1149-1155). online: ACM.
    DOI Scopus17
    2018 Dong, L., Gan, Y., Mao, X., Yang, Y., & Shen, C. (2018). Learning Deep Representations Using Convolutional Auto-Encoders with Symmetric Skip Connections. In ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings Vol. 2018-April (pp. 3006-3010). online: IEEE.
    DOI Scopus8 WoS4
    2018 Zhang, J., Wu, Q., Shen, C., Zhang, J., Lu, J., & van den Hengel, A. (2018). Goal-oriented visual question generation via intermediate rewards. In V. Ferrari, M. Hebert, C. Sminchisescu, & Y. Weiss (Eds.), Computer Vision - ECCV 2018: Proceedings, Part V Vol. Lecture Notes in Computer Science; vol. 11209 (pp. 189-204). Munich: Springer.
    DOI Scopus5 WoS3
    2018 Nekrasov, V., Shen, C., & Reid, I. D. (2018). Light-Weight RefineNet for Real-Time Semantic Segmentation. In BMVC (pp. 1-15). Northumbria University, Newcastle upon Tyne: BMVA Press.
    Scopus10
    2018 Ma, C., Shen, C., Dick, A., Wu, Q., Wang, P., Van Den Hengel, A., & Reid, I. (2018). Visual Question Answering with memory-augmented network. In Proceedings: 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR 2018) (pp. 6975-6984). Salt Lake City, Utah: IEEE.
    DOI Scopus37 WoS21
    2018 Zhuang, B., Wu, Q., Shen, C., Reid, I., & Van Den Hengel, A. (2018). HCVRD: A benchmark for large-scale human-centered visual relationship detection. In 32nd AAAI Conference on Artificial Intelligence, AAAI 2018 (pp. 7631-7638). New Orleans: Association for the Advancement of Artificial Intelligence.
    Scopus12 WoS4
    2018 Zhang, J., Wu, Q., Zhang, J., Shen, C., & Lu, J. (2018). Kill two birds with one stone: Weakly-supervised neural network for image annotation and tag refinement. In 32nd AAAI Conference on Artificial Intelligence, AAAI 2018 (pp. 7550-7557). New Orleans: ASSOC ADVANCEMENT ARTIFICIAL INTELLIGENCE.
    Scopus4 WoS3
    2018 Chen, Y., Tai, Y., Liu, X., Shen, C., & Yang, J. (2018). FSRNet: End-to-End Learning Face Super-Resolution with Facial Priors. In Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition (pp. 2492-2501). Salt Lake City, UT: IEEE.
    DOI Scopus164 WoS88
    2018 Wu, Q., Wang, P., Shen, C., Reid, I., & Hengel, A. (2018). Are you talking to me? Reasoned visual dialog generation through adversarial learning. In Proceedings: 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR 2018) (pp. 6106-6115). Salt Lake City, UT: IEEE.
    DOI Scopus50 WoS17
    2018 Song, Y., Ma, C., Wu, X., Gong, L., Bao, L., Zuo, W., . . . Yang, M. (2018). VITAL: VIsual Tracking via Adversarial Learning. In Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition (pp. 8990-8999). online: IEEE.
    DOI Scopus241 WoS146
    2018 Xian, K., Shen, C., Cao, Z., Lu, H., Xiao, Y., Li, R., & Luo, Z. (2018). Monocular Relative Depth Perception with Web Stereo Data Supervision. In Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition (pp. 311-320). online: IEEE.
    DOI Scopus49 WoS22
    2018 Wang, X., Xiao, T., Jiang, Y., Shao, S., Sun, J., & Shen, C. (2018). Repulsion Loss: Detecting Pedestrians in a Crowd. In Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition (pp. 7774-7783). online: IEEE.
    DOI Scopus195 WoS98
    2018 Shen, T., Lin, G., Shen, C., & Reid, I. (2018). Bootstrapping the performance of webly supervised semantic segmentation. In Proceedings of the 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR 2018) (pp. 1363-1371). Piscataway, NJ.: IEEE.
    DOI Scopus32 WoS5
    2017 Shen, T., Lin, G., Liu, L., Shen, C., & Reid, I. (2017). Weakly supervised semantic segmentation based on web image co-segmentation. In British Machine Vision Conference 2017, BMVC 2017 (pp. 1-12). online: BMVC.
    Scopus15
    2017 Wang, P., Wu, Q., Shen, C., Dick, A., & Van Den Hengel, A. (2017). Explicit knowledge-based reasoning for visual question answering. In C. Sierra (Ed.), Proceedings of the twenty-sixth International Joint Conference on Artificial Intelligence Vol. 0 (pp. 1290-1296). online: IJCAI.
    DOI Scopus43
    2017 Wei, X., Zhang, C., Li, Y., Xie, C., Wu, J., Shen, C., & Zhou, Z. (2017). Deep descriptor Transforming for image co-localization. In IJCAI International Joint Conference on Artificial Intelligence Vol. 0 (pp. 3048-3054). USA: AAAI Press.
    DOI Scopus12
    2017 Lin, G., Milan, A., Shen, C., & Reid, I. (2017). RefineNet: multi-path refinement networks with identity mappings for high-resolution semantic segmentation. In Proceedings: 30th IEEE Conference on Computer Vision and Pattern Recognition Vol. 2017-January (pp. 5168-5177). online: IEEE.
    DOI Scopus1059 WoS619
    2017 Zhuang, B., Liu, L., Li, Y., Shen, C., & Reid, I. (2017). Attend in groups: a weakly-supervised deep learning framework for learning from web data. In Proceedings of the 30th IEEE Conference on Computer Vision and Pattern Recognition (CVPR 2017) Vol. 2017-January (pp. 2915-2924). Online: IEEE.
    DOI Scopus29 WoS74
    2017 Gong, D., Yang, J., Liu, L., Zhang, Y., Reid, I., Shen, C., . . . Shi, Q. (2017). From motion blur to motion flow: a deep learning solution for removing heterogeneous motion blur. In Proceedings of the 30th IEEE Conference on Computer Vision and Pattern Recognition (CVPR 2017) Vol. 2017-January (pp. 3806-3815). Online: IEEE.
    DOI Scopus130 WoS46
    2017 Chen, Z., Jacobson, A., Sunderhauf, N., Upcroft, B., Liu, L., Shen, C., . . . Milford, M. (2017). Deep Learning Features at Scale for Visual Place Recognition. In Proceedings - IEEE International Conference on Robotics and Automation (pp. 3223-3230). Online: IEEE.
    DOI Scopus125
    2017 Shen, T., Lin, G., Shen, C., & Reid, I. (2017). Learning Multi-level Region Consistency with Dense Multi-label Networks for Semantic Segmentation. In Proceedings of International Joint Conference on Artificial Intelligence IJCAI Vol. 0 (pp. 2708-2714). Online: International Joint Conferences on Artificial Intelligence.
    DOI Scopus4
    2017 Li, H., Wang, P., & Shen, C. (2017). Towards End-to-End Text Spotting with Convolutional Recurrent Neural Networks. In Proceedings of the IEEE International Conference on Computer Vision Vol. 2017-October (pp. 5248-5256). Venice, ITALY: IEEE.
    DOI Scopus73 WoS50
    2017 Lu, H., Zhang, L., Cao, Z., Wei, W., Xian, K., Shen, C., & Hengel, A. (2017). When Unsupervised Domain Adaptation Meets Tensor Representations. In Proceedings: 2017 IEEE International Conference on Computer Vision Vol. 2017-October (pp. 599-608). Venice, Italy: IEEE.
    DOI Scopus33 WoS3
    2017 Chen, Y., Shen, C., Wei, X., Liu, L., & Yang, J. (2017). Adversarial PoseNet: a structure-aware convolutional network for human pose estimation. In Proceedings of the IEEE International Conference on Computer Vision (ICCV 2017) Vol. 2017 (pp. 1221-1230). Piscataway, NJ: IEEE.
    DOI Scopus139 WoS69
    2017 Liu, W., Chen, X., Shen, C., Liu, Z., & Yang, J. (2017). Semi-Global Weighted Least Squares in Image Filtering. In Proceedings of the IEEE International Conference on Computer Vision Vol. 2017-October (pp. 5862-5870). online: IEEE.
    DOI Scopus15 WoS6
    2017 Zhuang, B., Liu, L., Shen, C., & Reid, I. (2017). Towards context-aware interaction recognition for visual relationship detection. In Proceedings 2017 IEEE International Conference on Computer Vision ICCV 2017 Vol. 2017-October (pp. 589-598). Venice, Italy: IEEE.
    DOI Scopus67 WoS33
    2017 Wang, P., Wu, Q., Shen, C., & van den Hengel, A. (2017). The VQA-machine: learning how to use existing vision algorithms to answer new questions. In Proceedings: 30th IEEE Conference on Computer Vision and Pattern Recognition Vol. 2017-January (pp. 3909-3918). Honolulu: IEEE.
    DOI Scopus50 WoS18
    2017 Wang, P., Liu, L., Shen, C., Huang, Z., van den Hengel, A., & Shen, H. (2017). Multi-attention network for one shot learning. In Proceedings of the 30th IEEE Conference on Computer Vision and Pattern Recognition (CVPR 2017) Vol. 2017-January (pp. 6212-6220). Online: IEEE.
    DOI Scopus49 WoS25
    2017 Li, Y., Lin, G., Zhuang, B., Liu, L., Shen, C., & van den Hengel, A. (2017). Sequential person recognition in photo albums with a recurrent network. In Proceedings: 30th IEEE Conference on Computer Vision and Pattern Recognition Vol. 2017-January (pp. 5660-5668). online: IEEE.
    DOI Scopus21 WoS5
    2017 McMahon, S., Shen, T., Sünderhauf, N., Reid, I., Shen, C., & Milford, M. (2017). Auxiliary tasks to improve trip hazard affordance detection on construction sites. In Australasian Conference on Robotics and Automation, ACRA Vol. 2017-December (pp. 124-132). Online: Australasian Robotics and Automation Association.
    Scopus1
    2016 Mao, X., Shen, C., & Yang, Y. (2016). Image restoration using very deep convolutional encoder-decoder networks with symmetric skip connections. In Proceedings of the 30th Annual Conference on Neural Information Processing Systems (NIPS 2016), as published in Advances in Neural Information Processing Systems Vol. 29 (pp. 2810-2818). Barcelona, Spain: Neural information Processing Systems Foundation.
    Scopus739 WoS100
    2016 Wang, P., Liu, L., Shen, C., Huang, Z., Van Den Hengel, A., & Shen, H. (2016). What's wrong with that object? Identifying images of unusual objects by modelling the detection score distribution. In Proceedings of the 29th IEEE Computer Society Conference on Computer Vision and Pattern Recognition Vol. 2016-December (pp. 1573-1581). Las Vegas, NV: IEEE.
    DOI Scopus7 WoS4
    2016 Wu, Q., Wang, P., Shen, C., Dick, A., & Van Den Hengel, A. (2016). Ask me anything: free-form visual question answering based on knowledge from external sources. In Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition Vol. 2016-December (pp. 4622-4630). Las Vegas, NV: IEEE.
    DOI Scopus178 WoS83
    2016 Qiao, R., Liu, L., Shen, C., & van den Hengel, A. (2016). Less is more: zero-shot learning from online textual documents with noise suppression. In Proceedings of the 29th IEEE Computer Society Conference on Computer Vision and Pattern Recognition Vol. 2016-December (pp. 2249-2257). Las Vegas, NV: IEEE.
    DOI Scopus90 WoS50
    2016 Zhuang, B., Lin, G., Shen, C., & Reid, I. (2016). Fast training of triplet-based deep binary embedding networks. In Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition Vol. 2016-December (pp. 5955-5964). Las Vegas, NV: IEEE.
    DOI Scopus81 WoS51
    2016 Lin, G., Shen, C., Van Den Hengel, A., & Reid, I. (2016). Efficient piecewise training of deep structured models for semantic segmentation. In Proceedings of the 29th IEEE Conference on Computer Vision and Pattern Recognition (CVPR 2016) Vol. 2016-December (pp. 3194-3203). Las Vegas, NV: IEEE.
    DOI Scopus470 WoS78
    2016 Wu, Q., Shen, C., Liu, L., Dick, A., & Van Den Hengel, A. (2016). What value do explicit high level concepts have in vision to language problems?. In Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition Vol. 2016-December (pp. 203-212). Las Vegas, NV: IEEE.
    DOI Scopus288 WoS168
    2016 Zhang, L., Wei, W., Zhang, Y., Shen, C., Van Den Hengel, A., & Shi, Q. (2016). Cluster sparsity field for hyperspectral imagery denoising. In B. Leibe, J. Matas, N. Sebe, & M. Welling (Eds.), Proceedings of the 14th European Conference on Computer Vision Vol. 9909 (pp. 631-647). Amsterdam, Netherlands: Springer International Publishing AG.
    DOI Scopus14 WoS11
    2016 Li, Y., Liu, L., Shen, C., & van den Hengel, A. (2016). Image co-localization by mimicking a good detector’s confidence score distribution. In B. Leibe, J. Matas, N. Sebe, & M. Welling (Eds.), Proceedings of the 14th European Conference on Computer Vision, Part II Vol. 9906 LNCS (pp. 19-34). Amsterdam, Netherlands: Springer International Publishing.
    DOI Scopus28 WoS20
    2016 Zhang, J., Zhang, J., Lu, J., Shen, C., Curr, K., Phua, R., . . . Edmonds, E. (2016). SLNSW-UTS: a historical image dataset for image multi-labeling and retrieval. In Proceedings of the International Conference on Digital Image Computing: Techniques and Applications (pp. 1-6). Gold Coast, Qld: IEEE.
    DOI Scopus2 WoS1
    2015 Shen, F., Shen, C., Liu, W., & Shen, H. (2015). Supervised discrete hashing. In Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition Vol. 07-12-June-2015 (pp. 37-45). Boston, MA: IEEE.
    DOI Scopus752 WoS556
    2015 Li, Y., Liu, L., Shen, C., & Van Den Hengel, A. (2015). Mid-level deep pattern mining. In Proceedings of the 2015 IEEE Computer Society Conference on Computer Vision and Pattern Recognition Vol. 07-12-June-2015 (pp. 971-980). Boston, MA: IEEE.
    DOI Scopus65 WoS38
    2015 Wang, P., Shen, C., & Van Den Hengel, A. (2015). Efficient SDP inference for fully-connected CRFs based on low-rank decomposition. In Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition Vol. 07-12-June-2015 (pp. 3222-3231). Boston, MA: IEEE.
    DOI Scopus11 WoS2
    2015 Tan, M., Shi, Q., Van Den Hengel, A., Shen, C., Gao, J., Hu, F., & Zhang, Z. (2015). Learning graph structure for multi-label image classification via clique generation. In Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition Vol. 07-12-June-2015 (pp. 4100-4109). Boston, MA: IEEE.
    DOI Scopus29 WoS20
    2015 Paisitkriangkrai, S., Shen, C., & Van Den Hengel, A. (2015). Learning to rank in person re-identification with metric ensembles. In Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition Vol. 07-12-June-2015 (pp. 1846-1855). Boston, MA: IEEE.
    DOI Scopus344 WoS235
    2015 Liu, L., Shen, C., & van den Hengel, A. (2015). The treasure beneath convolutional layers: cross-convolutional-layer pooling for image classification. In Proceedings of the 2015 IEEE Computer Society Conference on Computer Vision and Pattern Recognition Vol. 07-12-June-2015 (pp. 4749-4757). Boston, MA: IEEE.
    DOI Scopus118 WoS70
    2015 Li, B., Shen, C., Dai, Y., Van Den Hengel, A., & He, M. (2015). Depth and surface normal estimation from monocular images using regression on deep features and hierarchical CRFs. In Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition Vol. 07-12-June-2015 (pp. 1119-1127). Boston, MA: IEEE.
    DOI Scopus324 WoS236
    2015 Milford, M., Lowry, S., Sunderhauf, N., Shirazi, S., Pepperell, E., Upcroft, B., . . . Reid, I. (2015). Sequence searching with deep-learnt depth for condition-and viewpoint-invariant route-based place recognition. In IEEE Conference on Computer Society Conference on Computer Vision and Pattern Recognition Workshops Vol. 2015-October (pp. 18-25). Boston, MA: IEEE.
    DOI Scopus30 WoS2
    2015 Lin, G., Shen, C., Reid, I., & Van Den Hengel, A. (2015). Deeply learning the messages in message passing inference. In C. Cortes, N. Lawrence, D. Lee, M. Sugiyama, & R. Garnett (Eds.), Advances in Neural Information Processing Systems 28: 29th Annual Conference on Neural Information Processing Systems 2015 Vol. 2015-January (pp. 361-369). Montreal: Neural Information Processing Systems.
    Scopus27
    2015 Zhang, L., Wei, W., Zhang, Y., Li, F., Shen, C., & Shi, Q. (2015). Hyperspectral Compressive Sensing Using Manifold-Structured Sparsity Prior. In Proceedings of the IEEE International Conference on Computer Vision (ICCV) Vol. 2015 International Conference on Computer Vision, ICCV 2015 (pp. 3550-3558). Santiago, Chile: IEEE.
    DOI Scopus13 WoS14
    2015 Liu, F., Shen, C., & Lin, G. (2015). Deep convolutional neural fields for depth estimation from a single image. In Proceedings of the 2015 IEEE Conference on Computer Vision and Pattern Recognition Vol. 07-12-June-2015 (pp. 5162-5170). Boston, MA: IEEE.
    DOI Scopus494 WoS312
    2014 Liu, L., Shen, C., Wang, L., Van Den Hengel, A., & Wang, C. (2014). Encoding high dimensional local features by sparse coding based fisher vectors. In Proceedings of the 27th International Conference on Neural Information Processing Systems Vol. 2 (pp. 1143-1151). Online: MIT Press.
    Scopus58 WoS1
    2014 Lin, G., Shen, C., & Wu, J. (2014). Optimizing ranking measures for compact binary code learning. In D. Fleet, T. Pajdla, B. Schiele, & T. Tuytelaars (Eds.), Computer Vision - ECCV 2014, 13th European Conference, Zurich, Switzerland, September 6-12, 2014: Proceedings, Part III Vol. 8691 LNCS (pp. 613-627). Zurich, Switzerland: Springer International Publishing.
    DOI Scopus13 WoS13
    2014 Paisitkriangkrai, S., Shen, C., & Van Den Hengel, A. (2014). Strengthening the effectiveness of pedestrian detection with spatially pooled features. In Computer Vision - ECCV 2014, 13th European Conference, Zurich, Switzerland, September 6-12, 2014: Proceedings, Part IV Vol. 8692 LNCS (pp. 546-561). Zurich, Switzerland: Springer International Publishing.
    DOI Scopus121 WoS99
    2014 Lin, G., Shen, C., Shi, Q., Van Den Hengel, A., & Suter, D. (2014). Fast supervised hashing with decision trees for high-dimensional data. In Proceedings of 2014 IEEE Conference on Computer Vision and Pattern Recognition (pp. 1971-1978). Columbus, Ohio: IEEE.
    DOI Scopus313 WoS202
    2013 Harandi, M., Sanderson, C., Shen, C., & Lovell, B. (2013). Dictionary learning and sparse coding on Grassmann manifolds: an extrinsic solution. In Proceedings of the 2013 IEEE International Conference on Computer Vision, ICCV 2013 (pp. 1-9). USA: IEEE Computer Society.
    DOI Scopus101 WoS77
    2013 Lin, G., Shen, C., Suter, D., & Van Den Hengel, A. (2013). A general two-step approach to learning-based hashing. In Proceedings of the 2013 IEEE International Conference on Computer Vision, ICCV 2013 (pp. 1-13). USA: IEEE Computer Society.
    DOI Scopus145 WoS97
    2013 Li, Y., Shen, C., Jia, W., & Van Den Hengel, A. (2013). Leveraging surrounding context for scene text detection. In Proceedings of the IEEE 2013 International Conference on Image Processing, ICIP 2013 (pp. 2264-2268). USA: IEEE.
    DOI Scopus14 WoS11
    2013 Li, X., Li, Y., Shen, C., Dick, A., & Van Den Hengel, A. (2013). Contextual hypergraph modeling for salient object detection. In Proceedings of the 2013 IEEE International Conference on Computer Vision, ICCV 2013 (pp. 3328-3335). USA: IEEE Computer Society.
    DOI Scopus170 WoS122
    2013 Lin, G., Shen, C., & Van Den Hengel, A. (2013). Approximate constraint generation for efficient structured boosting. In Proceedings of the 2013 IEEE International Conference on Image Processing (pp. 4287-4291). USA: IEEE.
    DOI
    2013 Zhang, C., Bastian, J., Shen, C., Van Den Hengel, A., & Shen, T. (2013). Extended depth-of-field via focus stacking and graph cuts. In Proceedings of the 2013 IEEE Conference on Image Processing, ICIP 2013 (pp. 1272-1276). USA: IEEE.
    DOI Scopus9 WoS10
    2013 Paisitkriangkrai, S., Shen, C., & Van Den Hengel, A. (2013). Efficient pedestrian detection by directly optimizing the partial area under the ROC curve. In Proceedings of the IEEE International Conference on Computer Vision, ICCV 2013 (pp. 1057-1064). USA: IEEE.
    DOI Scopus39 WoS19
    2013 Li, X., Lin, G., Shen, C., Van Den Hengel, A., & Dick, A. (2013). Learning hash functions using column generation. In Proceedings of the 30th International Conference on Machine Learning, IMLS 2013 (pp. 1-9). online: IMCL.
    Scopus102
    2013 Yao, R., Shi, Q., Shen, C., Zhang, Y., & Van Den Hengel, A. (2013). Part-based visual tracking with online latent structural learning. In Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition (pp. 2363-2370). United States of America: IEEE.
    DOI Scopus191 WoS143
    2013 Wang, Z., Shi, Q., Shen, C., & Van Den Hengel, A. (2013). Bilinear programming for human activity recognition with unknown MRF graphs. In Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition (pp. 1690-1697). United States of America: IEEE.
    DOI Scopus29 WoS11
    2013 Shen, F., Shen, C., Shi, Q., Van Den Hengel, A., & Tang, Z. (2013). Inductive hashing on manifolds. In Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition (pp. 1562-1569). United States of America: IEEE.
    DOI Scopus186 WoS140
    2013 Wang, P., Shen, C., & Van Den Hengel, A. (2013). A fast semidefinite approach to solving binary quadratic problems. In Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition (pp. 1312-1319). United States: IEEE.
    DOI Scopus18 WoS7
    2013 Li, X., Shen, C., Dick, A., & Van Den Hengel, A. (2013). Learning compact binary codes for visual tracking. In Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition (pp. 2419-2426). United States: IEEE.
    DOI Scopus75 WoS56
    2012 Lin, G., Shen, C., Van Den Hengel, A., & Suter, D. (2012). Fast training of effective multi-class boosting using coordinate descent optimization. In Proceedings of the 11th Asian Conference on Computer Vision, ACCV 2012 Vol. 7725 LNCS (pp. 782-793). Germany: Springer-Verlag.
    DOI
    2012 Yao, R., Shi, Q., Shen, C., Zhang, Y., & Van Den Hengel, A. (2012). Robust tracking with weighted online structured learning. In Proceedings of the 2012 European Conference on Computer Vision, ECCV 2012 Vol. 7574 LNCS (pp. 158-172). Germany: Springer-Verlag.
    DOI Scopus24 WoS21
    2012 Paisitkriangkrai, S., Shen, C., & Van Den Hengel, A. (2012). Sharing features in multi-class boosting via group sparsity. In Proceedings of 2012 IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2012 (pp. 2128-2135). USA: IEEE.
    DOI Scopus6 WoS3
    2012 Li, X., Shen, C., Shi, Q., Dick, A., & Van Den Hengel, A. (2012). Non-sparse linear representations for visual tracking with online reservoir metric learning. In Proceedings of the 2012 IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2012 (pp. 1760-1767). USA: IEEE.
    DOI Scopus68 WoS41
    2012 Shi, Q., Shen, C., Hill, R., & Van Den Hengel, A. (2012). Is margin preserved after random projection?. In Proceedings of the29th International Conference on Machine Learning, ICML 12 Vol. 1 (pp. 591-598). USA: Omnipress.
    Scopus29
    2011 Li, H., Shen, C., & Shi, Q. (2011). Real-time visual tracking using compressive sensing. In Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition (pp. 1305-1312). Online: IEEE.
    DOI Scopus308 WoS216
    2011 Wang, P., Shen, C., Barnes, N., Zheng, H., & Ren, Z. (2011). Asymmetric totally-corrective boosting for real-time object detection. In Computer Vision ¿ ACCV 2010, Lecture Notes in Computer Science, Volume 6492 Vol. 6492 LNCS (pp. 176-188). New York: Springer.
    DOI Scopus4
    2011 Wang, L., Shen, C., & Hartley, R. (2011). On the optimality of sequential forward feature selection using class separability measure. In Proceedings International Conference on Digital Image Computing: Techniques and Applications (DICTA'11), 2011 (pp. 203-208). USA: IEEE.
    DOI Scopus9
    2011 Wang, T., He, X., Shen, C., & Barnes, N. (2011). Laplacian margin distribution boosting for learning from sparsely labeled data. In Proceedings of International Conference on on Digital Image Computing: Techniques and Applications (DICTA'11), 2011. (pp. 209-216). USA: IEEE.
    DOI
    2011 Liu, L., Wang, L., & Shen, C. (2011). A generalized probabilistic framework for compact codebook creation. In Proceedings IEEE Conference on Computer Vision and Pattern Recognition (pp. 1537-1544). USA: IEEE.
    DOI Scopus9 WoS6
    2011 Shen, C., & Hao, Z. (2011). A direct formulation for totally-corrective multi-class boosting. In Proceedings IEEE Conference on Computer Vision and Pattern Recognition (pp. 2585-2592). USA: IEEE.
    DOI Scopus19
    2011 Shen, C., Kim, J., & Wang, L. (2011). A scalable dual approach to semidefinite metric learning. In Proceedings of IEEE Conference on Computer Vision and Pattern Recognition (pp. 2601-2608). USA: IEEE.
    DOI Scopus25
    2011 Park, K., Shen, C., Hao, Z., & Kim, J. (2011). Efficiently learning a distance metric for large margin nearest neighbor classification. In Proceedings of the Twenty-Fifth AAAI Conference on Artificial Intelligence Vol. 1 (pp. 453-458). online: AAAI Press.
    Scopus15
    2011 Paisitkriangkrai, S., Shen, C., & Zhang, J. (2011). Face detection with effective feature extraction. In Proceedings of the 2010 Asian Conference on Computer Vision; Lecture Notes in Computer Science, vol. 6494, no, 3 Vol. 6494 (pp. 460-470). Heidelberger Platz 3 Berlin Germany D-14197: Springer-Verlag Berlin.
    DOI Scopus9 WoS2
    2011 Li, X., Dick, A., Wang, H., Shen, C., & Van Den Hengel, A. (2011). Graph mode-based contextual kernels for robust SVM tracking. In Proceedings of IEEE International Conference on Computer Vision (ICCV), 2011 (pp. 1156-1163). USA: IEEE.
    DOI Scopus35 WoS27
    2011 Shi, Q., Eriksson, A., Van Den Hengel, A., & Shen, C. (2011). Is face recognition really a compressive sensing problem?. In Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition (pp. 553-560). USA: IEEE.
    DOI Scopus257 WoS174
    2011 Zheng, Y., Shen, C., Hartley, R., & Huang, X. (2011). Pyramid center-symmetric local binary/trinary patterns for effective pedestrian detection. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) Vol. 6495 LNCS (pp. 281-292). Springer Berlin Heidelberg.
    DOI Scopus34
    2011 Hao, Z., Shen, C., Barnes, N., & Wang, B. (2011). Totally-corrective multi-class boosting. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) Vol. 6495 LNCS (pp. 269-280). Springer Berlin Heidelberg.
    DOI Scopus3
    2010 Shen, C., Wang, P., & Li, H. (2010). LACBoost and FisherBoost: Optimally building cascade classifiers. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) Vol. 6312 LNCS (pp. 608-621). Springer Berlin Heidelberg.
    DOI Scopus10
    2010 Wang, P., Shen, C., Zheng, H., & Ren, Z. (2010). A variant of the trace quotient formulation for dimensionality reduction. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) Vol. 5996 LNCS (pp. 277-286). Springer Berlin Heidelberg.
    DOI Scopus2
    2010 Shi, Q., Li, H., & Shen, C. (2010). Rapid face recognition using hashing. In Proceedings of 23rd IEEE Computer Society Conference on Computer Vision and Pattern Recognition (pp. 2753-2760). USA: IEEE.
    DOI Scopus39
    2010 Shen, C., Wang, P., & Li, H. (2010). LACBoost and FisherBoost: optimally building cascade classifiers. In Proc. European Conference on Computer Vision (ECCV'10) (pp. 608-621). NewYork: Springer Berlin Heidelberg.
    DOI
    2010 Zhou, L., Wang, L., Shen, C., & Barnes, N. (2010). Hippocampal shape classification using redundancy constrained feature selection. In Proc. International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI'10), Lecture Notes in Computer Science, Volume 6362 Vol. 6362 LNCS (pp. 266-273). New York: Springer.
    DOI Scopus4
    2010 Wang, W., Zhang, J., & Shen, C. (2010). Improved human detection and classification in thermal images. In Proceedings of 2010 IEEE 17th International Conference on Image Processing (ICIP 2010) (pp. 2313-2316). Hong Kong: IEEE.
    DOI Scopus51
    2010 Wang, P., Shen, C., Zheng, H., & Ren, Z. (2010). Training a multi-exit cascade with linear asymmetric classification for efficient object detection. In Proceedings of 2010 IEEE 17th IEEE International Conference on Image Processing (ICIP 2010) (pp. 61-64). Hong Kong: IEEE.
    DOI Scopus5
    2010 Li, H., Wang, P., & Shen, C. (2010). Robust face recognition via accurate face alignment and sparse representation. In Proc. International Conference on on Digital Image Computing: Techniques and Applications (DICTA'10) (pp. 262-269). Online: IEEE.
    DOI Scopus5
    2009 Wang, W., Shen, C., Zhang, J., & Paisitkriangkrai, S. (2009). A two-layer night-time vehicle detector. In Proceedings International Conference on Digital Image Computing - Techniques and Applications (DICTA'09), 2009 (pp. 162-167). Online: IEEE.
    DOI Scopus23 WoS18
    2009 Dai, Y., Li, H., He, M., & Shen, C. (2009). Smooth Approximation of L-infinity-Norm for Multi-view Geometry. In Proceedings of International Conference on Digital Image Computing - Techniques and Applications (DICTA'09), 2009 (pp. 339-346). Online: IEEE.
    DOI Scopus4
    2009 Paisitkriangkrai, S., Shen, C., & Zhang, J. (2009). Efficiently training a better visual detector with sparse eigenvectors. In Proceedings IEEE Conference on Computer Vision and Pattern Recognition (CVPR'09) (pp. 1-12). Online: IEEE.
    DOI
    2009 Wang, P., Shen, C., Zheng, H., & Ren, Z. (2009). A variant of the trace quotient formulation for dimensionality reduction. In H. Zha, R. Taniguchi, & S. Maybank (Eds.), Proceedings of 9th Asian Conference on Computer Vision 2009 : LNCS 5996 (pp. 277-286). Berlin: Springer-Verlag.
    DOI
    2009 Kim, J., Shen, C., & Wang, P. (2009). A scalable algorithm for learning a Mahalanobis distance metric. In Proceedings of 9th Asian Conference on Computer Vision (ACCV'09), 2009 Vol. 5996 LNCS (pp. 299-310). New York: Springer Berlin Heidelberg.
    DOI Scopus6
    2009 Zhang, J., Paisitkriangkrai, S., & Shen, C. (2009). An overview of fast pedestrian detection: feature selection and cascade framework of boosted features. In IEEE International Converence on Multimedia and Expo (pp. 1566-1567). Online: IEEE.
    DOI Scopus2 WoS1
    2009 Shen, C., Kim, J., Wang, L., & Van Den Hengel, A. (2009). Positive Semidefinite Metric Learning with Boosting. In Proceedings of NIPS 2009 (pp. 1651-1660). online: NIPS.
    Scopus61
    2009 Paisitkriangkrai, S., Shen, C., & Zhang, J. (2009). Efficiently training a better visual detectorwith sparse eigenvectors. In 2009 IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops, CVPR Workshops 2009 Vol. 2009 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (pp. 1129-1136). IEEE.
    DOI Scopus11
    2008 Wang, L., Zhou, L., & Shen, C. (2008). A fast algorithm for creating a compact and discriminative visual codebook. In Computer Vision - ECCV 2008: 10th European Conference on Computer Vision, Marseille, France, October 12-18, 2008, Proceedings, Part IV Vol. 5305 LNCS (pp. 719-732). New York: Springer.
    DOI Scopus16
    2008 Paisitkriangkrai, S., Shen, C., & Zhang, J. (2008). An experimental study on pedestrian classification using local features. In IEEE International Symposium on Circuits and Systems, 2008 (pp. 2741-2744). Online: IEEE.
    DOI Scopus10 WoS4
    2008 Paisitkriangkrai, S., Shen, C., & Zhang, J. (2008). Real-time pedestrian detection using a boosted multi-layer classifier. In VS 2008 - The Eighth International Workshop on Visual Surveillance, in conjunction with European Conference on Computer Vision (ECCV'08) (pp. 1-8). Marseille, France.
    2008 Shen, C., Welsh, A., & Wang, L. (2008). PSDBoost: matrix-generation linear programming for positive semidefinite matrices learning. In Advances in Neural Information Processing Systems 21 (pp. 1473-1480). Vancouver, British Columbia, Canada: Curran Associates, Inc.
    Scopus25
    2008 Shen, C., Paisitkriangkrai, S., & Zhang, J. (2008). Face detection from few training examples. In Proceedings of IEEE International Conference on Image Processing (ICiP'08) (pp. 2764-2767). Online: IEEE.
    DOI Scopus11 WoS9
    2008 Lu, Y., Wang, L., Hartley, R., Li, H., & Shen, C. (2008). Multi-view human motion capture with an improved deformation skin model. In Proceedings of International Conference on Digital Image Computing - Techniques and Applications (DICTA'08) (pp. 420-427). Online: IEEE.
    DOI Scopus8
    2008 Kim, J., Shen, C., & Wang, L. (2008). Learning cascaded reduced - set SVMs using linear programming. In Digital Image Computing - Techniques and Applications (DICTA'08) (pp. 619-626). Online: IEEE.
    DOI
    2008 Shen, C., Li, H., & Brooks, M. (2008). Self-calibrating cameras using semidefinite programming. In Proceedings of the International Conference on Digital Image Computing - Techniques and Applications (DICTA'08) (pp. 436-441). Online: IEEE.
    DOI
    2008 Li, H., & Shen, C. (2008). Boosting the minimum margin: LPBoost vs. AdaBoost. In Proceedings International Conference on Digital Image Computing - Techniques and Applications (DICTA'08) (pp. 533-539). Online: IEEE.
    DOI Scopus12
    2007 Paisitkriangkrai, S., Shen, C., & Zhang, J. (2007). An experimental evaluation of local features for pedestrian classification. In 9th Biennial Conference of the Australian Pattern Recognition Society on Digital Image Computing Techniques and Applications (pp. 53-60). Online: IEEE Computer Society.
    DOI Scopus8
    2007 Shen, C., & Wen, Z. (2007). Color image labelling using linear programming. In Proceedings International Conference on Digital Image Computing - Techniques and Applications (DICTA'07) (pp. 239-244). Online: IEEE.
    DOI
    2007 Nguyen, Q., Robles-Kelly, A., & Shen, C. (2007). Kernel-based tracking from a probabilistic viewpoint. In Proceedings of IEEE Conference on Computer Vision and Pattern Recognition (CVPR'07) (pp. 1-8). Online: IEEE.
    DOI Scopus10
    2007 Shen, C., Li, H., & Brooks, M. (2007). Feature extraction using sequential semidefinite programming. In M. Bottema (Ed.), Proceedings of DICTA 2007 (pp. 430-437). CDROM: IEEE.
    DOI Scopus3
    2007 Shen, C., Li, H., & Brooks, M. (2007). A convex programming approach to the trace quotient problem. In Yasushi Yagi (Ed.), Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 4844 LNCS (PART 2) Vol. 4844 LNCS (pp. 227-235). Germany: Springer.
    DOI Scopus10 WoS12
    2006 Shen, C., Li, H., & Brooks, M. (2006). Classification-based likelihood functions for Bayesian tracking. In M. Piccardi, & T. Hintz (Eds.), Proceedings of AVSS 2006 (pp. CDROM1-CDROM6). CDROM: IEEE.
    DOI Scopus1
    2006 Nguyen, Q., Robles-Kelly, A., & Shen, C. (2006). Enhanced kernel-based tracking for monochromatic and thermographic video. In Proc. IEEE International Conference on Advanced Video and Signal based Surveillance (AVSS'06) (pp. 1-6). Online: IEEE.
    DOI Scopus10
    2006 Li, H., & Shen, C. (2006). An LMI approach for reliable PTZ camera self-calibration. In IEEE International Conference on Video and Signal based Surveillance (AVSS'06) (pp. 1-6). Online: IEEE.
    DOI Scopus14
    2005 Shen, C., Van Den Hengel, A., & Brooks, M. (2005). Visual tracking via efficient kernel discriminant subspace learning. In C. Regazzoni, & F. De Natale (Eds.), Proceedings of the IEEE International Conference on Image Processing Vol. 2 (pp. 1-4). USA: IEEE.
    DOI Scopus7
    2005 Shen, C., Brooks, M., & Van Den Hengel, A. (2005). Augmented particle filtering for efficient visual tracking. In C. Regazzoni, & F. De Natale (Eds.), Proceedings of the IEEE International Conference on Image Processing Vol. 3 (pp. 1-4). USA: IEEE.
    DOI Scopus7 WoS3
    2005 Shen, C., Brooks, M., & Van Den Hengel, A. (2005). Fast global kernel density mode seeking with application to localisation and tracking. In S. Ma, & H. Shum (Eds.), Proceedings of the Tenth IEEE International Conference on Computer Vision Vol. II (pp. 1516-1523). Los Alamitos, California: IEEE.
    DOI Scopus35 WoS18
    2005 Shen, C., & Brooks, M. (2005). Adaptive over-relaxed mean shift. In A. Bouzerdoum, & A. Beghdadi (Eds.), Proceedings of the 8th International Symposium on Signal Processing and its Applications Vol. 2 (pp. 575-578). USA: IEEE.
    DOI Scopus5
    2004 Shen, C., Van Den Hengel, A., Dick, A., & Brooks, M. (2004). Enhanced importance sampling: Unscented auxiliary particle filtering for visual tracking. In G. Webb, & X. Yu (Eds.), Proceedings of the 17th Australasian Joint Conference on Artificial Intelligence 2004 Vol. 3339 (pp. 180-191). Berlin, Germany: Springer.
    DOI Scopus9 WoS5
    2004 Shen, C., Van Den Hengel, A., Dick, A., & Brooks, M. (2004). 2D articulated tracking with dynamic Bayesian networks. In D. Wei, H. Wang, Z. Peng, A. Kara, & Y. He (Eds.), Proceedings of the 4th International Conference on Computer and Information Technology 2004 (pp. 1-7). Los Alamitos, California, USA: IEEE.
    DOI Scopus8 WoS6
    2003 Shen, C., Van Den Hengel, A., & Dick, A. (2003). Probabilistic multiple cue intergration for particle filter based tracking. In C. Sun, H. Talbot, S. Ourselin, & T. Adriaansen (Eds.), Proceedings of the 7th Biennial Australian Pattern Recognition Society Conference - DICTA 2003 (pp. 399-408). Australia: CSIRO.

SA State Government through its Research Consortia Program under the Premier’s Research and Industry Fund

  • 2018-2022, Unlocking complex resources through lean processing, $8.6m (relinquished Jan. 2021)

Australian Research Council (ARC) Grants:

  1. 2020-2022 DP, "Deep learning that scales", $390k (relinquished Jan. 2021)
  2. 2020-2023, "ARC industrial transformation training centre for integrated operations for complex resources", $5.7m (relinquished Jan. 2021)
  3. 2018-2023, "ARC industrial transformation research hub for driving farming productivity and disease prevention", $8.8m (relinquished Jan. 2021)
  4. 2019 LIEF, "A world-class machine learning facility for Australia", $700k
  5. 2016 LIEF, "Computational infrastructure for developing deep machine learning models", $250k
  6. 2014-2021 ARC Centre of Excellence, "Australian Centre for Robotic Vision", $20m
  7. 2013 LIEF, "Computational infrastructure for machine learning in computer vision", $210k
  8. 2013 LP, "Semantic change detection through large-scale learning", $380k
  9. 2012 LP, "Scalable classification for massive datasets: randomised algorithms", $510k
  10. 2012-2016 Future Fellowship (step 2), "Continuously learning to see", $650k
  11. 2010 LIEF, "Accelerating Australia's large scale video surveillance research programmes", $280k

Cooperative Research Centre (CRC) Grants:

  • 2017-2019 CRC Project, "Intelligent vision, sensing and data fusion for mining and exploration", $4.6m
    CIs: Prof. C. Shen, Prof. Nigel Cook, Dr. Damith Ranasinghe
  • 2014-2018, Data to Decisions CRC Project Grant, ID: 0001038181, "Large scale image classification", $946k
    CIs: Prof. A. van den Hengel, Prof. C. Shen, Dr A. Dick, Dr A. Eriksson, Dr Q. Shi
  • 2014-2018, Data to Decisions CRC Project Grant, ID: 0001038182, "Exploiting contextual cues in large-scale machine learning", $1.15m
    CIs: Prof. A. van den Hengel, Prof. C. Shen, Dr A. Dick, Dr Q. Shi

Cure Brain Cancer Foundation’s Infrastructure Grant:

  • 2018-2020,  "A national brain-organoid based high-throughput platform for personalised drug and genetic screening in glioblastoma", $400k (with Guillermo Gomez et al.; 1 of the 5 CIs)

Industry Grants:

  • 2020 Adobe gift
    Sole CI
  • 2017-2019 UA170942 "Research and development of computer vision and deep learning technologies for the development of a novel intelligent ultrasound cardiothoracic assessment tool", Contracting Party: an Australian start-up company, $605,628
    CIs: Prof.  A. van den Hengel, Prof. C. Shen
  • 2017-2018 UA171194 "Research on deep learning for computational photography", Contracting Party: a leading mobile phone manufacturer, US$70k
    Sole CI
  • 2018-2020 UA182751 "Research on basic algorithms in computational photography",  Contracting Party: a leading mobile phone manufacturer, $863,038
    Sole CI
  • 2018-2019 UA183176 "Scene understanding via multi-task learning", $246,000
    Sole CI

Miscellaneous:

  • 2019,  "Development of new hydrogels to selectively extract and kill invasive glioblastoma cells from normal brain tissue", Partner Investigator (with Guillermo Gomez et al.)

Grant information on Research Data

Check http://cs.adelaide.edu.au/~chhshen/teaching.html for updated information

  Mining Big Data Course code: COMPSCI 4403
  Introduction to Statistical Machine Learning Course code: COMPSCI 4401/7401
  Algorithm and Data Structure Analysis (Small-Group Discovery Experience) Course code: COMPSCI 2201
  Operating Systems Course code: COMPSCI 3004NA/7064NA
  Computer Graphics Course code: COMPSCI 3014NA
  Scientific Computing (Small-Group Discovery Experience) Course code: COMPSCI 1012
  Introduction to Statistical Machine Learning Course code: COMPSCI 7012
  Master of Computing and Innovation Project Course code: COMPSCI 7098
  Foundations of Computer Science Course code: COMPSCI 2202
  Computer Vision Course code: COMPSCI 4022/7022

  

    Expand

  • Current Higher Degree by Research Supervision (University of Adelaide)
    Date Role Research Topic Program Degree Type Student Load Student Name
    2021 Co-Supervisor Joint Grouping and Labeling is Solved by Using Graphical Models Doctor of Philosophy Doctorate Full Time Miss Jinchao Ge
    2021 Principal Supervisor Computer Vision Doctor of Philosophy Doctorate Full Time Mr Yongtao Ge
    2021 Principal Supervisor Efficient deep-learning based dynamic neural representational decoders for high-resolution semanticsegmentation Doctor of Philosophy Doctorate Full Time Mr Bowen Zhang
    2020 Principal Supervisor Text Visual Question Answering Doctor of Philosophy Doctorate Full Time Mr Xinyu Wang
    2020 Principal Supervisor Total Scene Understanding Using Deep Learning Doctor of Philosophy Doctorate Full Time Mr Yunzhi Zhuge
    2020 Principal Supervisor Deep learning for high-performance instance recognition Doctor of Philosophy Doctorate Full Time Mr Xinlong Wang
    2020 Principal Supervisor Computer vision, object detection Master of Philosophy Master Full Time Mr Weian Mao
    2020 Principal Supervisor Weakly Supervised Semantic Segmentation Doctor of Philosophy Doctorate Full Time Mr Choubo Ding
    2019 Co-Supervisor Computer Vision Geometry Deep Learning Doctor of Philosophy Doctorate Full Time Mr Jiawang Bian
    2019 Principal Supervisor Semantic 3D Scene Reconstruction Doctor of Philosophy Doctorate Full Time Mr Libo Sun
    2018 Principal Supervisor Semantic Understanding Based on 3D Data Doctor of Philosophy Doctorate Full Time Mr Wei Yin
    2018 Principal Supervisor Multi-modality Data Analysis Using Deep Learning Doctor of Philosophy Doctorate Full Time Mr Hu Wang
    2018 Principal Supervisor Instance Level Object Segmentation in Video using Deep Learning Doctor of Philosophy Doctorate Full Time Ms Yutong Dai
    2018 Principal Supervisor High Performance Per Pixel Prediction Using Deep Learning Doctor of Philosophy Doctorate Full Time Ms Yifan Liu

  • Past Higher Degree by Research Supervision (University of Adelaide)
    Date Role Research Topic Program Degree Type Student Load Student Name
    2018 - 2019 Principal Supervisor High-performance Object Detection and Tracking using Deep Learning Master of Philosophy Master Full Time Mr Xinyu Wang
    2018 - 2021 Principal Supervisor Fully Convolutional Instance-level Visual Recognition Doctor of Philosophy Doctorate Full Time Mr Zhi Tian
    2017 - 2020 Co-Supervisor Semantic Image Segmentation and Other Dense Per-Pixel Tasks: Practical Approaches Doctor of Philosophy Doctorate Full Time Mr Vladimir Nekrasov
    2017 - 2021 Principal Supervisor Efficient Fully-Convolutional Networks for Image Perception Doctor of Philosophy Doctorate Full Time Mr Hao Chen
    2017 - 2020 Principal Supervisor Efficient Scene Parsing with Imagery and Point Cloud Data Doctor of Philosophy Doctorate Full Time Mr Tong He
    2016 - 2020 Co-Supervisor How Geometry Meets Learning in Pose Estimation Doctor of Philosophy Doctorate Full Time Mr Ming Cai
    2016 - 2017 Principal Supervisor Deep Learning for Fine-Gained Visual Recognition Master of Philosophy Master Full Time Mr Teng Li
    2015 - 2017 Principal Supervisor Sketch Image Recognition Using Deep Features Master of Philosophy Master Full Time Miss Yuchao Jiang
    2015 - 2019 Principal Supervisor Context Learning and Weakly Supervised Learning for Semantic Segmentation Doctor of Philosophy Doctorate Full Time Mr Tong Shen
    2014 - 2018 Principal Supervisor Text Detection and Recognition in Natural Scene Images Doctor of Philosophy Doctorate Full Time Mrs Hui Li
    2014 - 2018 Principal Supervisor Towards Efficient Deep Neural Networks with Applications to Visual Recognition Doctor of Philosophy Doctorate Full Time Dr Bohan Zhuang
    2014 - 2017 Principal Supervisor Deep Visual Representation for Weakly-supervised and Structured Output Tasks Doctor of Philosophy Doctorate Full Time Mr Yao Li
    2014 - 2016 Principal Supervisor Deep Learning for Multi-label Scene Classification Master of Philosophy Master Full Time Mr Junjie Zhang
    2013 - 2017 Principal Supervisor Dynamic Scene Understanding with Applications to Traffic Monitoring Doctor of Philosophy Doctorate Full Time Mr Qichang Hu
    2013 - 2018 Principal Supervisor Deep Learning Based RGB-D Vision Tasks Doctor of Philosophy Doctorate Full Time Mr Yuanzhouhan Cao
    2013 - 2018 Principal Supervisor Mid-level Representations for Action Recognition and Zero-shot Learning Doctor of Philosophy Doctorate Full Time Mr Ruizhi Qiao
    2012 - 2014 Principal Supervisor Structured Output Prediction and Binary Code Learning in Computer Vision Doctor of Philosophy Doctorate Full Time Dr Guosheng Lin
    2012 - 2014 Principal Supervisor Hypergraph Modeling for Saliency Detection and Beyond Master of Engineering Science Master Full Time Mr Yao Li
    2011 - 2015 Principal Supervisor Learning Structured Prediction Models in Computer Vision Doctor of Philosophy Doctorate Full Time Miss Fayao Liu
  • Position: Professor
  • Phone: 83136745
  • Email: chunhua.shen@adelaide.edu.au
  • Fax: 8313 4366
  • Campus: North Terrace
  • Building: Australian Institute for Machine Learning, floor 1
  • Room: 1.05.A
  • Org Unit: Australian Institute for Machine Learning
Connect With Me
External Profiles