Professor Chunhua Shen

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• Appointments

  Date	Position	Institution name
  2011	Senior Lecturer/Associate Professor/Professor	University of Adelaide
  2005 - 2011	Researcher/Senior Researcher	National ICT Australia

• 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 - 2006	The University of Adelaide	Australia	PhD
  —	Nanjing University	China	Master
  —	Nanjing University	China	Bachelor

• Research Interests

  Computer Graphics Computer Vision Knowledge Representation and Machine Learning

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• Journals

  Year	Citation
  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 Scopus4 WoS2
  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 Scopus1 WoS1
  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
  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 Scopus6 WoS5
  2019	Zhang, L., Wang, P., Shen, C., Liu, L., Wei, W., Zhang, Y., & van den Hengel, A. (2019). Adaptive Importance Learning for Improving Lightweight Image Super-Resolution Network. International Journal of Computer Vision, 21 pages. DOI
  2019	Li, H., Wang, P., Shen, C., & Zhang, G. (2019). Show, Attend and Read: A Simple and Strong Baseline for Irregular Text Recognition. THIRTY-THIRD AAAI CONFERENCE ON ARTIFICIAL INTELLIGENCE / THIRTY-FIRST INNOVATIVE APPLICATIONS OF ARTIFICIAL INTELLIGENCE CONFERENCE / NINTH AAAI SYMPOSIUM ON EDUCATIONAL ADVANCES IN ARTIFICIAL INTELLIGENCE, 8610-8617.
  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
  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 Scopus13 WoS8
  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
  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 WoS3
  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 Scopus1 WoS1
  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
  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 Scopus1
  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
  2018	Liu, W., Zhang, P., Chen, X., Shen, C., Huang, X., & Yang, J. (2018). Embedding Bilateral Filter in Least Squares for Efficient Edge-preserving Image Smoothing. IEEE Transactions on Circuits and Systems for Video Technology. DOI
  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 Scopus6 WoS6
  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. DOI
  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 Scopus6 WoS6
  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 Scopus21
  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 Scopus5 WoS4
  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 Scopus1
  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 Scopus11 WoS7
  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 Scopus27 WoS31
  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 Scopus16 WoS6
  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 Scopus8 WoS2
  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 Scopus14
  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 Scopus25 WoS18
  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 Scopus10 WoS8
  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 Scopus13 WoS10
  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 Scopus12 WoS11 Europe PMC2
  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 Scopus23
  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 Scopus12 WoS6
  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 Scopus78 WoS62
  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 Scopus9 WoS7
  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 Scopus11 WoS8
  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 Scopus35 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 Scopus7 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 Scopus3
  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 Scopus26 WoS18
  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 Scopus7 WoS5
  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 Scopus13 WoS11 Europe PMC3
  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 Scopus4 WoS4
  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 Scopus4
  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 Scopus7 WoS7
  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 Scopus28 WoS19
  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 Scopus27 WoS22
  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 Scopus8 WoS8
  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 Scopus20 WoS13 Europe PMC2
  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 Scopus16 WoS20 Europe PMC1
  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 Scopus8 WoS6
  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 Scopus55 WoS44 Europe PMC4
  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 Scopus2
  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 Scopus31 WoS21
  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 Scopus17 WoS15
  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 Scopus233 WoS151 Europe PMC15
  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 Scopus4
  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	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 Scopus3 WoS4
  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 Scopus30 WoS22
  2016	Li, H., Shen, F., Shen, C., Yang, Y., & Gao, Y. (2016). Face recognition using linear representation ensembles. Pattern Recognition, 59, 72-87. DOI Scopus12 WoS7
  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 Scopus36
  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 Scopus11
  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 Scopus87 WoS79 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 Scopus90 WoS71
  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 Scopus4 WoS4
  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 Scopus46 WoS36 Europe PMC6
  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 Scopus10 WoS4
  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 Scopus10 WoS6 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 Scopus22 WoS21 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 Scopus41
  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 Scopus7
  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 Scopus52 WoS45 Europe PMC21
  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 Scopus57 WoS44 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 WoS11
  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 Scopus73 WoS55 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 Scopus15 WoS12
  2013	Shen, C., Li, H., & Van Den Hengel, A. (2013). Fully corrective boosting with arbitrary loss and regularization. Neural Networks, 48, 44-58. DOI Scopus6 WoS4 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 Scopus24 WoS26 Europe PMC4
  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 Scopus24 WoS18
  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, In Press(10), 1-9. DOI Scopus24 WoS24
  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 Scopus466 WoS407
  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 Scopus22 WoS17
  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. Scopus59 WoS44
  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 Scopus29 WoS26 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 Scopus33 WoS30 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 Scopus23 WoS19 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 Scopus10 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 Scopus75 WoS59
  2010	Shen, C. (2010). On the dual formulation of boosting algorithms. IEEE Transactions on Pattern Analysis and Machine Intelligence, 32(12), 2216-2231. DOI
  2010	Shen, C., & Li, H. (2010). Boosting through optimization of margin distributions. IEEE Transactions on Neural Networks, 21(4), 659-666. DOI
  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
  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
  2010	Li, H., & Shen, C. (2010). Interactive color image segmentation with linear programming. Machine Vision and Applications, 21(4), 403-412. DOI
  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 Scopus38 WoS30
  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 Scopus105
  2008	Shen, C., Li, H., & Brooks, M. (2008). Supervised dimensionality reduction via sequential semidefinite programming. Pattern Recognition, 41(12), 3644-3652. DOI Scopus21 WoS20
  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 Scopus169 WoS118 Europe PMC14
  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 Scopus66 WoS48 Europe PMC4
  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 Scopus13 Europe PMC2
  —	Zhuang, B., Liu, L., Shen, C., & Reid, I. (n.d.). Towards Context-aware Interaction Recognition.
  —	Chen, Y., Shen, C., Chen, H., Wei, X. -S., Liu, L., & Yang, J. (n.d.). Adversarial Learning of Structure-Aware Fully Convolutional Networks for Landmark Localization.
  —	Zhuang, B., Shen, C., & Reid, I. (n.d.). Training Compact Neural Networks with Binary Weights and Low Precision Activations.
  —	Nekrasov, V., Chen, H., Shen, C., & Reid, I. (n.d.). Fast Neural Architecture Search of Compact Semantic Segmentation Models via Auxiliary Cells.
  —	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.
  —	Zhang, H., Li, Y., Chen, H., & Shen, C. (n.d.). IR-NAS: Neural Architecture Search for Image Restoration.
  —	Zhang, X., Zhang, R., Cao, J., Gong, D., You, M., & Shen, C. (n.d.). Part-Guided Attention Learning for Vehicle Re-Identification.
  —	Zhuang, B., Shen, C., Tan, M., Liu, L., & Reid, I. (n.d.). Structured Binary Neural Networks for Image Recognition.
  —	Zhang, H., Shen, C., Li, Y., Cao, Y., Liu, Y., & Yan, Y. (n.d.). Exploiting temporal consistency for real-time video depth estimation.
  —	Zhuang, B., Liu, J., Tan, M., Liu, L., Reid, I., & Shen, C. (n.d.). Effective Training of Convolutional Neural Networks with Low-bitwidth Weights and Activations.
  —	Lu, H., Dai, Y., Shen, C., & Xu, S. (n.d.). Indices Matter: Learning to Index for Deep Image Matting.
  —	Lu, H., Dai, Y., Shen, C., & Xu, S. (n.d.). Index Network.
  —	Yin, W., Liu, Y., Shen, C., & Yan, Y. (n.d.). Enforcing geometric constraints of virtual normal for depth prediction.
  —	Zhang, X., Cao, J., Shen, C., & You, M. (n.d.). Self-training with progressive augmentation for unsupervised cross-domain person re-identification.
  —	Li, H., Wang, P., & Shen, C. (n.d.). Towards End-to-End Text Spotting in Natural Scenes.
  —	Li, H., Wang, P., Shen, C., & Hengel, A. V. D. (n.d.). Visual Question Answering as Reading Comprehension.
  —	Zhang, H., Li, Y., Wang, P., Liu, Y., & Shen, C. (n.d.). RGB-D Based Action Recognition with Light-weight 3D Convolutional Networks.
  —	Zhuang, B., Shen, C., Tan, M., Liu, L., & Reid, I. (n.d.). Structured Binary Neural Networks for Accurate Image Classification and Semantic Segmentation.
  —	Wang, X., Liu, S., Shen, X., Shen, C., & Jia, J. (n.d.). Associatively Segmenting Instances and Semantics in Point Clouds.
  —	He, T., Shen, C., Tian, Z., Gong, D., Sun, C., & Yan, Y. (n.d.). Knowledge Adaptation for Efficient Semantic Segmentation.
  —	Tian, Z., He, T., Shen, C., & Yan, Y. (n.d.). Decoders Matter for Semantic Segmentation: Data-Dependent Decoding Enables Flexible Feature Aggregation.
  —	Zhuang, B., Liu, L., Tan, M., Shen, C., & Reid, I. (n.d.). Training Quantized Network with Auxiliary Gradient Module.
  —	Tian, Z., Shen, C., Chen, H., & He, T. (n.d.). FCOS: Fully Convolutional One-Stage Object Detection.

• Conference Papers

  Year	Citation
  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 - IEEE International Conference on Robotics and Automation Vol. 2019-May (pp. 7101-7107). online: IEEE. DOI
  2019	Li, R., Xian, K., Shen, C., Cao, Z., Lu, H., & Hang, L. (2019). Deep Attention-Based Classification Network for Robust Depth Prediction. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) Vol. 11364 LNCS (pp. 663-678). Online: Springer Verlag. DOI
  2019	Wei, X., Zhang, C., Liu, L., Shen, C., & Wu, J. (2019). Coarse-to-Fine: A RNN-Based Hierarchical Attention Model for Vehicle Re-identification. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) Vol. 11362 LNCS (pp. 575-591). Switzerland: Springer. DOI
  2019	Pang, G., Shen, C., & Van Den Hengel, A. (2019). Deep anomaly detection with deviation networks. In Proceedings of the ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (pp. 353-362). online: ASSOC COMPUTING MACHINERY. DOI
  2019	Cai, M., Shen, C., & Reid, I. (2019). A hybrid probabilistic model for camera relocalization. In British Machine Vision Conference 2018, BMVC 2018 (pp. 1-12). online: BMVC.
  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. Scopus2
  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.
  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 Scopus22 WoS7
  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 Scopus4
  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 Scopus5 WoS3
  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). Scopus1
  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. Scopus1
  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. Scopus7
  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). Calgary. DOI
  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
  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 Scopus9 WoS5
  2018	Zhuang, B., Shen, C., Tan, M., Liu, L., & Reid, I. (2018). Towards Effective Low-Bitwidth Convolutional Neural Networks. In Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition (pp. 7920-7928). DOI Scopus5
  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 Scopus1
  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 20418 (pp. 6975-6984). Salt Lake City, Utah: IEEE. DOI Scopus3 WoS1
  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 (pp. 1290-1296). online: IJCAI. DOI Scopus12
  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 (pp. 3048-3054). Melbourne. Scopus4
  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). Honolulu: IEEE. DOI Scopus261 WoS54
  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 Scopus8 WoS11
  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 Scopus22 WoS4
  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. DOI Scopus28
  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 (pp. 2708-2714). Online: International Joint Conferences on Artificial Intelligence. Scopus2
  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 Scopus16 WoS5
  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 Scopus9 WoS2
  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 Scopus43 WoS17
  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). Venice, ITALY: IEEE. DOI Scopus7 WoS3
  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 Scopus13 WoS3
  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 Scopus18 WoS3
  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 Scopus14 WoS6
  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). Honolulu: IEEE. DOI Scopus9 WoS2
  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
  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. Scopus6
  2016	Mao, X., Shen, C., & Yang, Y. (2016). Image restoration using very deep convolutional encoder-decoder networks with symmetric skip connections. In Advances in Neural Information Processing Systems. 30th Annual Conference on Neural Information Processing Systems, NIPS 2016 (pp. 2810-2818). Online: Neural information processing systems foundation. Scopus258
  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 Scopus6 WoS3
  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 Scopus98 WoS40
  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 Scopus47 WoS28
  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 Scopus46 WoS23
  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 Scopus240 WoS7
  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 Scopus179 WoS83
  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 Scopus10 WoS9
  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 Scopus15 WoS11
  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	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 Scopus11 WoS12
  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. Scopus20
  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 Scopus434 WoS295
  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 Scopus52 WoS30
  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 Scopus8 WoS1
  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 Scopus16 WoS9
  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 Scopus248 WoS147
  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 Scopus267
  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 Scopus90 WoS48
  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 Scopus150 WoS84
  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 Scopus17
  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. Scopus49 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 Scopus8
  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 Scopus94 WoS74
  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 Scopus220 WoS90
  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 Scopus75
  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 Scopus114 WoS74
  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 Scopus129 WoS92
  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 Scopus8 WoS7
  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 Scopus33 WoS17
  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. Scopus82
  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 Scopus173 WoS125
  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 Scopus17 WoS5
  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 Scopus150 WoS106
  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 Scopus17 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 Scopus70 WoS51
  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 Scopus21 WoS19
  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 Scopus65 WoS38
  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. Scopus27
  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 Scopus286 WoS190
  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 (pp. 176-188). New York: Springer. DOI
  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
  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 Scopus24
  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 Scopus7 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 Scopus32 WoS19
  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 Scopus238 WoS161
  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 Scopus33
  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 (pp. 266-273). New York: Springer. DOI
  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
  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
  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
  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 Scopus22 WoS17
  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
  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 (pp. 299-310). New York: Springer Berlin Heidelberg. DOI
  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. Scopus52
  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 (pp. 719-732). New York: Springer. DOI
  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.
  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 WoS8
  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
  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
  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
  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
  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 Scopus9 WoS9
  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
  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
  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
  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 WoS9
  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 WoS2
  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.

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

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• Current Higher Degree by Research Supervision (University of Adelaide)

  Date	Role	Research Topic	Program	Degree Type	Student Load	Student Name
  2019	Principal Supervisor	Semantic 3D Scene Reconstruction	Doctor of Philosophy	Doctorate	Full Time	Mr Libo Sun
  2019	Co-Supervisor	Computer Vision Geometry Deep Learning	Doctor of Philosophy	Doctorate	Full Time	Mr Jiawang Bian
  2018	Principal Supervisor	Towards Real-World Application: Fast High-performance Semantic Segmentation	Doctor of Philosophy	Doctorate	Full Time	Mr Zhi Tian
  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
  2017	Co-Supervisor	Attention Mechanisms and Methods for Semantic Image Segmentation	Doctor of Philosophy	Doctorate	Full Time	Mr Vladimir Nekrasov
  2017	Principal Supervisor	Text detection and Recognition in the wild	Doctor of Philosophy	Doctorate	Full Time	Mr Tong He
  2017	Principal Supervisor	Intelligent Dialogue Agent for Software Engineering	Doctor of Philosophy	Doctorate	Full Time	Mr Hao Chen
  2016	Co-Supervisor	Long Term Semantic Scene Understanding and Slam	Doctor of Philosophy	Doctorate	Full Time	Mr Ming Cai

• 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
  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	Mr 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 - 2018	Principal Supervisor	Mid-level Representations for Action Recognition and Zero-shot Learning	Doctor of Philosophy	Doctorate	Full Time	Mr Ruizhi Qiao
  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
  2012 - 2014	Principal Supervisor	Hypergraph Modeling for Saliency Detection and Beyond	Master of Engineering Science	Master	Full Time	Mr Yao Li
  2012 - 2014	Principal Supervisor	Structured Output Prediction and Binary Code Learning in Computer Vision	Doctor of Philosophy	Doctorate	Full Time	Dr Guosheng Lin
  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: Ingkarni Wardli, floor 5
• Org Unit: School of Computer Science