Dr Lingqiao Liu
Senior Lecturer
School of Computer and Mathematical Sciences
Faculty of Sciences, Engineering and Technology
Eligible to supervise Masters and PhD - email supervisor to discuss availability.
Dr. Lingqiao Liu is a Senior Lecturer and ARC DECRA Fellow in School of Computer Science, University of Adelaide, Australia. He obtained his P.h.D. from the Australian National University in 2014. He is a recipient of ARC DECRA (Discovery Early Career Researcher Award) award in 2016 and the University of Adelaide Research Fellowship award in 2016. He has a broad research interest in machine learning, computer vision and natural language processing. More information about me can be found in my home page
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Journals
Year Citation 2022 Zhuang, B., Shen, C., Tan, M., Chen, P., Liu, L., & Reid, I. (2022). Structured Binary Neural Networks for Image Recognition. INTERNATIONAL JOURNAL OF COMPUTER VISION, 130(9), 22 pages.
Scopus1 WoS12022 Wang, X., Liu, L., & Shi, J. Q. (2022). Computationally Efficient Dilated Convolutional Model for Melody Extraction. IEEE Signal Processing Letters, 29, 1599-1603.
2022 Shu, Y., Li, Q., Liu, L., & Xu, G. (2022). Privileged multi-task learning for attribute-aware aesthetic assessment. Pattern Recognition, 132, 108921.
Scopus12022 Yang, L., Wang, Y., Liu, L., Wang, P., & Zhang, Y. (2022). Center Prediction Loss for Re-identification. Pattern Recognition, 132, 11 pages.
Scopus12022 Xu, H. M., Liu, L., & Abbasnejad, E. (2022). Progressive Class Semantic Matching for Semi-supervised Text Classification. NAACL 2022 - 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Proceedings of the Conference, 3003-3013. 2022 Liu, D., Wu, L., Zheng, F., Liu, L., & Wang, M. (2022). Verbal-Person Nets: Pose-Guided Multi-Granularity Language-to-Person Generation. IEEE Transactions on Neural Networks and Learning Systems, PP, 13 pages.
Scopus1 WoS22022 Zhou, Y., Song, X., Zhang, Y., Liu, F., Zhu, C., & Liu, L. (2022). Feature Encoding With Autoencoders for Weakly Supervised Anomaly Detection. IEEE Transactions on Neural Networks and Learning Systems, 33(6), 2454-2465.
Scopus14 Europe PMC22021 Kang, L., Liu, J., Liu, L., Zhou, Z., & Ye, D. (2021). Semi-supervised emotion recognition in textual conversation via a context-augmented auxiliary training task. Information Processing and Management, 58(6), 1-13.
Scopus12021 Shu, Y., Li, Q., Liu, L., & Xu, G. (2021). Semi-supervised Adversarial Learning for Attribute-Aware Photo Aesthetic Assessment. IEEE Transactions on Multimedia, 1-11.
Scopus32021 Lei, Y., Liu, Y., Zhang, P., & Liu, L. (2021). Towards using count-level weak supervision for crowd counting. Pattern Recognition, 109, 1-13.
Scopus19 WoS152021 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, 44(10), 6140-6152.
Scopus5 WoS32021 Peng, D., Lei, Y., Liu, L., Zhang, P., & Liu, J. (2021). Global and Local Texture Randomization for Synthetic-to-Real Semantic Segmentation. IEEE Transactions on Image Processing, 30, 6594-6608.
Scopus5 WoS32021 Su, H., Wang, P., Liu, L., Li, H., Li, Z., & Zhang, Y. (2021). Where to Look and How to Describe: Fashion Image Retrieval with an Attentional Heterogeneous Bilinear Network. IEEE Transactions on Circuits and Systems for Video Technology, 31(8), 3254-3265.
Scopus8 WoS72021 Lu, W., Gong, D., Fu, K., Sun, X., Diao, W., & Liu, L. (2021). Boundarymix: Generating pseudo-training images for improving segmentation with scribble annotations. Pattern Recognition, 117, 107924.
Scopus5 WoS32021 Zhang, J., Liu, L., Wang, P., & Zhang, J. (2021). Exploring the auxiliary learning for long-tailed visual recognition. Neurocomputing, 449, 303-314.
Scopus3 WoS22020 Abbasnejad, M. E., Shi, Q., van den Hengel, A., & Liu, L. (2020). GADE: A Generative Adversarial Approach to Density Estimation and its Applications. International Journal of Computer Vision, 128(10-11), 2731-2743.
Scopus2 WoS12020 Jiang, S., Lu, X., Lei, Y., & Liu, L. (2020). Mask-Aware Networks for Crowd Counting. IEEE Transactions on Circuits and Systems for Video Technology, 30(9), 3119-3129.
Scopus142020 Gou, Y., Lei, Y., Liu, L., Zhang, P., & Peng, X. (2020). A Dynamic Parameter Enhanced Network for distant supervised relation extraction. Knowledge-Based Systems, 197, 1-12.
Scopus72020 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.
Scopus12 WoS9 Europe PMC12020 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.
Scopus18 WoS212020 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.
Scopus30 WoS232020 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.
Scopus17 WoS172019 Teney, D., Wang, P., Cao, J., Liu, L., Shen, C., & Hengel, A. V. D. (2019). V-PROM: A Benchmark for Visual Reasoning Using Visual Progressive Matrices.. CoRR, abs/1907.12271, 12071-12078.
WoS22019 Wei, X. S., 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.
Scopus67 WoS44 Europe PMC12019 Wang, P., Liu, L., Shen, C., & Shen, H. T. (2019). Order-aware convolutional pooling for video based action recognition. Pattern Recognition, 91, 357-365.
Scopus14 WoS132019 Lei, Y., Zhou, Z., Zhang, P., Guo, Y., Ma, Z., & Liu, L. (2019). Deep point-to-subspace metric learning for sketch-based 3D shape retrieval. Pattern Recognition, 96, 106981-1-106981-13.
Scopus19 WoS182018 Chen, Z., Liu, L., Sa, I., Ge, Z., & Chli, M. (2018). Learning Context Flexible Attention Model for Long-Term Visual Place Recognition. IEEE Robotics and Automation Letters, 3(4), 4015-4022.
Scopus562017 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.
Scopus30 WoS232017 Liu, L., Wang, P., Shen, C., Wang, L., Van Den Hengel, A., Wang, C., & Shen, H. T. (2017). Compositional model based Fisher vector coding for image classification. IEEE Transactions on Pattern Analysis and Machine Intelligence, 39(12), 2335-2348.
Scopus46 WoS35 Europe PMC32017 Wang, L., Liu, L., & Zhou, L. (2017). A graph-embedding approach to hierarchical visual word mergence. IEEE Transactions on Neural Networks and Learning Systems, 28(2), 308-320.
Scopus3 WoS42017 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.
Scopus46 WoS422016 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.
Scopus60 WoS49 Europe PMC62016 Zhou, L., Wang, L., Liu, L., Ogunbona, P., & Shen, D. (2016). Learning discriminative Bayesian networks from high-dimensional continuous neuroimaging data. IEEE Transactions on Pattern Analysis and Machine Intelligence, 38(11), 2269-2283.
Scopus212016 Wang, P., Cao, Y., Shen, C., Liu, L., & Shen, H. T. (2016). Temporal pyramid pooling based convolutional neural network for action recognition. IEEE Transactions on Circuits and Systems for Video Technology, 27(99), 1-8.
Scopus88 WoS872016 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.
Scopus3 WoS22015 Wang, C., Wang, L., & Liu, L. (2015). Density maximization for improving graph matching with its applications. IEEE Transactions on Image Processing, 24(7), 2110-2123.
Scopus10 WoS8 Europe PMC12014 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.
Scopus13 WoS9 Europe PMC12013 Liu, X., Yin, J., Wang, L., Liu, L., Liu, J., Hou, C., & Zhang, J. (2013). An adaptive approach to learning optimal neighborhood kernels. IEEE Transactions on Cybernetics, 43(1), 371-384.
Scopus232012 Liu, X., Wang, L., Yin, J., & Liu, L. (2012). Incorporation of radius-info can be simple with SimpleMKL. Neurocomputing, 89, 30-38.
Scopus20- Qiao, R., Liu, L., Shen, C., & Hengel, A. V. D. (n.d.). Visually Aligned Word Embeddings for Improving Zero-shot Learning. -
Book Chapters
Year Citation 2014 Wang, L., Liu, L., Zhou, L., & Chan, K. L. (2014). Application of SVMs to the bag-of-features model: A kernel perspective. In Support Vector Machines Applications (Vol. 9783319023007, pp. 155-189). Springer International Publishing.
Scopus32014 Zhou, L., Wang, L., Liu, L., Ogunbona, P., & Shen, D. (2014). Support vector machines for neuroimage analysis: Interpretation from discrimination. In Support Vector Machines Applications (Vol. 9783319023007, pp. 191-220). Springer International Publishing.
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Conference Papers
DE170101259 (ARC Discovery Early Career Researcher Award 17): Zero-shot
and few-shot learning with deep knowledge transfer
DP160103710 (ARC Discovery Project 16) : Whole image understanding by
convolutions on graphs
Introduction to Statistic Machine Learning, Puzzle based Learning, Big Data Analysis and Project, Artificial Intelligence
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Current Higher Degree by Research Supervision (University of Adelaide)
Date Role Research Topic Program Degree Type Student Load Student Name 2023 Co-Supervisor Semi-supervised object detection for mobile robots Master of Philosophy Master Full Time Mr Xiangyu Shi 2022 Co-Supervisor Improving the Few-Shot Generalization of Data-to-Text Generation Models Doctor of Philosophy Doctorate Full Time Mr Xuan Ren 2021 Principal Supervisor Deep Learning, 3D Shape Analysis, Few-shot Learning, Low-supervised Learning, Natural Language Processing Doctor of Philosophy Doctorate Full Time Miss Ziqin Zhou 2021 Principal Supervisor Computer Vision, Computational Photography, Machine Learning Doctor of Philosophy Doctorate Full Time Mr Liang Chen 2021 Co-Supervisor Data efficient learning Doctor of Philosophy Doctorate Full Time Mr Yuhao Lin 2020 Principal Supervisor An Investigation into Unsupervised and Semi-Unsupervised Approaches to Crowd Counting Master of Philosophy Master Part Time Mr Avraham Nisel Chapman 2019 Co-Supervisor Machine Learning and Natural Language Processing in Stock Prediction Doctor of Philosophy Doctorate Full Time Mr Jinan Zou 2019 Principal Supervisor Unsupervised learning in Natural Language Processing Doctor of Philosophy Doctorate Part Time Mr Qiaoyang Luo -
Past Higher Degree by Research Supervision (University of Adelaide)
Date Role Research Topic Program Degree Type Student Load Student Name 2020 - 2023 Co-Supervisor Deep Learning for Multipitch Detection and Melody Extraction Doctor of Philosophy Doctorate Part Time Mr Xian Wang 2018 - 2019 Co-Supervisor High-performance Object Detection and Tracking using Deep Learning Master of Philosophy Master Full Time Mr Xinyu Wang 2018 - 2022 Principal Supervisor Deep Semi-Supervised Learning Methodologies and Applications Doctor of Philosophy Doctorate Full Time Mr Hai-Ming Xu 2018 - 2021 Co-Supervisor Deep Learning for 2D and 3D Scene Understanding Doctor of Philosophy Doctorate Full Time Mr Yu Liu 2017 - 2019 Co-Supervisor Context Learning and Weakly Supervised Learning for Semantic Segmentation Doctor of Philosophy Doctorate Full Time Mr Tong Shen 2017 - 2020 Co-Supervisor Efficient Scene Parsing with Imagery and Point Cloud Data Doctor of Philosophy Doctorate Full Time Mr Tong He 2017 - 2021 Co-Supervisor Deep Learning for Image Deblurring and Reflection Removal Doctor of Philosophy Doctorate Full Time Mr Jie Yang 2014 - 2018 Co-Supervisor Mid-level Representations for Action Recognition and Zero-shot Learning Doctor of Philosophy Doctorate Full Time Mr Ruizhi Qiao 2014 - 2018 Co-Supervisor Deep Learning Based RGB-D Vision Tasks Doctor of Philosophy Doctorate Full Time Mr Yuanzhouhan Cao
Connect With Me
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