About 

Ling Shao was the Founding CEO and Chief Scientist of the Inception Institute of Artificial Intelligence (IIAI), Abu Dhabi, UAE. He was the initiator of the world's first AI university - Mohamed bin Zayed University of Artificial Intelligence (MBZUAI), for which he served as the Founding Provost and Executive Vice President (2019-2021). He received his B.Eng. degree in Electronic and Information Engineering from the University of Science and Technology of China (USTC), his M.Sc. degree in Medical Image Analysis and his Ph.D. (D.Phil.) degree in Computer Vision from the University of Oxford. Previously, He was Chair Professor (2016-2018) in Computer Vision and Machine Learning with the University of East Anglia, Norwich, UK,  Chair Professor (2014-2016) in Computer Vision and Machine Intelligence with Northumbria University, Newcastle upon Tyne, UK, a Senior Lecturer (2009-2014) with the University of Sheffield, UK and a Senior Scientist (2005-2009) with Philips Research, The Netherlands. His research interests include Computer Vision, Deep Learning, Medical Imaging, and Vision and Language. He has authored/co-authored over 400 papers in top conferences/journals such as CVPR, ICCV, ECCV, NeurIPS, ICML, ICLR, TPAMI and IJCV and over 20 EU/US patents.

Shao served as an editorial board member of IEEE Transactions on Image Processing, IEEE Transactions on Neural Networks and Learning Systems, IEEE Transactions on Circuits and Systems for Video Technology, IEEE Transactions on Cybernetics, and several other journals. He has edited four books and several special issues for journals such as IJCV and Pattern Recognition. He was the General Chair for BMVC 2018, and an Area Chair or Program Committee member for many top conferences, including ICCV, CVPR, ECCV and ACM MM. He was selected as a 'Highly Cited Researcher' by the Web of Science (Thomson Reuters) in 2018/2019/2020. He is a Fellow of the IEEE, a Fellow of the IAPR, a Fellow of the British Computer Society, a Fellow of the IET, and a Life Member of the ACM. He was elected as a Member of the Mohammed bin Rashid Academy of Scientists (the National Academy of the UAE) in 2021.

 

News

Experience

Education

Publications (Refer to his Google Scholar profile for more updated publications)

 

Selected Journal Articles

 

D. Fan, G. Ji, M. Chen and L. Shao, Concealed Object Detection, IEEE Transactions on Pattern Analysis and Machine Intelligence, doi://10.1109/TPAMI.2021.3085766, in press, 2021.

 

H. Xiong, M. Yu, L. Liu, F. Zhu, J. Qin, F. Shen and L. Shao, A Generalized Method for Binary Optimization: Convergence Analysis and Applications, IEEE Transactions on Pattern Analysis and Machine Intelligence, doi://10.1109/TPAMI.2021.3070753, in press, 2021.

 

J. Cao, J. Xie, Y. Pang, F. Khan and L. Shao, From Handcrafted to Deep Features for Pedestrian Detection: A Survey, IEEE Transactions on Pattern Analysis and Machine Intelligence, doi://10.1109/TPAMI.2021.3076733, in press, 2021.

 

Y. Yan, J. Qin, B. Ni, J. Chen, L. Liu, F. Zhu, W-S. Zheng, X. Yang and L. Shao, Learning Multi-Attention Context Graph for Group-Based Re-Identification, IEEE Transactions on Pattern Analysis and Machine Intelligence, doi://10.1109/TPAMI.2020.3032542, in press, 2020.

 

M. Ye, J. Shen, G. Lin, T. Xiang, L. Shao and S. Hoi, Deep Learning for Person Re-identification: A Survey and Outlook, IEEE Transactions on Pattern Analysis and Machine Intelligence, doi: 10.1109/TPAMI.2021.3054775, in press, 2021.

 

H. Cholakkal, G. Sun, S. Khan, F. S. Khan, L. Shao and L. V. Gool, Towards Partial Supervision for Generic Object Counting in Natural Scenes, IEEE Transactions on Pattern Analysis and Machine Intelligence, doi://10.1109/TPAMI.2020.3021025, in press, 2020.

 

A. Mustafa, S. H. Khan, M. Hayat, R. Goecke, J. Shen and L. Shao, Deeply Supervised Discriminative Learning for Adversarial Defense, IEEE Transactions on Pattern Analysis and Machine Intelligence, doi://10.1109/TPAMI.2020.2978474, in press, 2020.

 

X. Dong, J. Shen, W. Wang, L. Shao, H. Ling and F. Porikli, Dynamical Hyperparameter Optimization via Deep Reinforcement Learning in Tracking, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 43, no. 5, pp. 1515-1529, 2021.

 

L. Shao, H. P. H. Shum, and T. M. Hospedales, Editorial: Special Issue on Machine Vision with Deep Learning, International Journal of Computer Vision, vol. 128, no. 4, pp. 771-772, 2020.

 

 J. Zhao, J. Han, L. Shao, and C. G. M. Snoek, Pixelated Semantic Colorization, International Journal of Computer Vision, vol. 128, no. 4, pp. 818-834, 2020.

 

 Y. Shen, L. Liu, and L. Shao, Unsupervised Binary Representation Learning with Deep Variational Networks, International Journal of Computer Vision, vol. 127, no. 11-12, pp. 1614-1628, 2019.

 

 Z. Zhang, L. Liu, F. Shen, H. T. Shen, and L. Shao, Binary Multi-View Clustering, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 41, no. 7, pp. 1774-1782, 2019.

 

F. Zheng, Y. Tang, and L. Shao, Hetero-Manifold Regularisation for Cross-Modal Hashing, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 40, no. 5, pp. 1059-1071, 2018.

 

 Y. Long, L. Liu, F. Shen, L. Shao, and X. Li, Zero-Shot Learning Using Synthesised Unseen Visual Data with Diffusion Regularisation, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 40, no. 10, pp. 2498-2512, 2018.

 

 L. Liu, M. Yu, and L. Shao, Latent Structure Preserving Hashing, International Journal of Computer Vision, vol. 122, no. 3, pp. 439-457, 2017.

 

L. Shao, L. Liu, and M. Yu, Kernelized Multiview Projection for Robust Action Recognition, International Journal of Computer Vision, vol. 118, no. 2, pp. 115-129, 2016.

 

 D. Wu, L. Pigou, P.-J. Kindermans, N. D.-H. Le, L. Shao, J. Dambre, and J.-M. Odobez, Deep Dynamic Neural Networks for Multimodal Gesture Segmentation and Recognition, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 38, no. 8, pp. 1583-1597, 2016.

 

 M. Yu, L. Liu, and L. Shao, Structure-Preserving Binary Representations for RGB-D Action Recognition, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 38, no. 8, pp. 1651-1664, 2016.

 

 M. Yu, L. Shao, X. Zhen, and X. He, Local Feature Discriminant Projection, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 38, no. 9, pp. 1908-1914, 2016.

 

 F. Zhu and L. Shao, Weakly-Supervised Cross-Domain Dictionary Learning for Visual Recognition, International Journal of Computer Vision, vol. 109, no. 1-2, pp. 42-59, 2014.

 

Selected Conference Papers

 

Mohammad Mahdi Derakhshani, Xiantong Zhen, Ling Shao and Cees Snoek, Kernel Continual Learning. Accepted by International Conference on Machine Learning (ICML), July 2021.

 

Zehao Xiao, Jiayi Shen, Xiantong Zhen, Ling Shao and Cees Snoek, A Bit More Bayesian: Domain-Invariant Learning with Uncertainty.  Accepted by International Conference on Machine Learning (ICML), July 2021.

 

Guo-Sen Xie, Jie Liu, Huan Xiong, Ling Shao, Scale-Aware Graph Neural Network for Few-Shot Semantic Segmentation. in IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.

 

Tianfei Zhou, Jianwu Li, Xueyi Li, Ling Shao, Target-Aware Object Discovery and Association for Unsupervised Video Multi-Object Segmentation. in IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.

 

Yunhua Zhang, Ling Shao, Cees G. M. Snoek, Repetitive Activity Counting by Sight and Sound. in IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.

 

Shujie Luo, Hang Dai, Ling Shao, Yong Ding, M3DSSD: Monocular 3D Single Stage Object Detector. in IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.

 

Qi Fan, Deng-Ping Fan, Huazhu Fu, Chi-Keung Tang, Ling Shao, Yu-Wing Tai, Group Collaborative Learning for Co-Salient Object Detection. in IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.

 

Irtiza Hasan, Shengcai Liao, Jinpeng Li, Saad Ullah Akram, Ling Shao, Generalizable Pedestrian Detection: The Elephant in the Room. in IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.

 

Lei Huang, Yi Zhou, Li Liu, Fan Zhu, Ling Shao, Group Whitening: Balancing Learning Efficiency and Representational Capacity. in IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.

 

Syed Waqas Zamir, Aditya Aroma, Salman Khan, Munawar Hayat, Fahad Shahbaz Khan, Ming-Hsuan Yang, Ling Shao, Multi-Stage Progressive Image Restoration. in IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.

 

Mingchen Zhuge, Dehong Gao, Deng-Ping Fan, Linbo Jin, Ben Chen, Haoming Zhou, Minghui Qiu, Ling Shao, Kaleido-BERT: Vision-Language Pre-Training on Fashion Domain. in IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.

 

Wencheng Han, Xingping Dong, Fahad Shahbaz Khan, Ling Shao, Jianbing Shen, Learning To Fuse Asymmetric Feature Maps in Siamese Trackers. in IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.

 

Yawen Huang, Feng Zheng, Danyang Wang, Weilin Huang, Matthew R. Scott, Ling Shao, Brain Image Synthesis With Unsupervised Multivariate Canonical CSCl4Net. in IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.

 

Yichao Yan, Jinpeng Li, Jie Qin, Song Bai, Shengcai Liao, Li Liu, Fan Zhu, Ling Shao, Anchor-Free Person Search. in IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.

 

Ying-Jun Du, Xiantong Zhen, Ling Shao, Cees Snoek, MetaNorm: Learning to Normalize Few-Shot Batches Across Domains. in International Conference on Learning Representations (ICLR), May 2021.

 

Xiantong Zhen, Ying-Jun Du, Huan Xiong, Qiang Qiu, Cees Snoek, Ling Shao, Learning to Learn Variational Semantic Memory. In Neural Information Processing Systems (NeurIPS), Dec. 6-12, 2020.

 

Fang Zhao, Shengcai Liao, Kaihao Zhang, and Ling Shao, Human Parsing Based Texture Transfer from Single Image to 3D Human via Cross-View Consistency. In Neural Information Processing Systems (NeurIPS), Dec. 6-12, 2020.

 

Huan Xiong, Lei Huang, Mengyang Yu, Li Liu, Fan Zhu, Ling Shao. On the Number of Linear Regions of Convolutional Neural Networks. In The Thirty-seventh International Conference on Machine Learning (ICML), 2020.

Xiantong Zhen, Haoliang Sun, Ying-Jun Du, Jun Xu, Yilong Yin, Ling Shao, Cees Snoek,
Learning to Learn Kernels with Variational Random Features. In The Thirty-seventh International Conference on Machine Learning (ICML), 2020.

 

Tao Zhou, Huazhu Fu, Chen Gong, Jianbing Shen, Ling Shao, Fatih Porikli. Multi-Mutual Consistency Induced Transfer Subspace Learning for Human Motion Segmentation. In IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2020.

 

Deng-Ping Fan, Ge-Peng Ji, Guolei Sun, Ming-Ming Cheng, Jianbing Shen, Ling Shao. Camouflaged Object Detection. In IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2020.

 

Y. Li, Y. Pang, J. Shen, J. Cao and L. Shao. NETNet: Neighbor Erasing and Transferring Network for Better Single Shot Object Detection. In IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2020.

 

Wenguan Wang, Hailong Zhu, Jifeng Dai, Yanwei Pang, Jianbing Shen, Ling Shao. Hierarchical Human Parsing With Typed Part-Relation Reasoning. In IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2020.

 

Lei Huang, Li Liu, Fan Zhu, Diwen Wan, Zehuan Yuan, Bo Li, Ling Shao. Controllable Orthogonalization in Training DNNs. In IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2020.

 

Lei Huang, Lei Zhao, Yi Zhou, Fan Zhu, Li Liu, Ling Shao. An Investigation into the Stochasticity of Batch Whitening. In IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2020.

 

Yuming Shen, Jie Qin, Jiaxin Chen, Mengyang Yu, Li Liu, Fan Zhu, Fumin Shen, Ling Shao. Auto-Encoding Twin-Bottleneck Hashing. In IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2020.

 

Yichao Yan, Jie Qin, Jiaxin Chen, Li Liu, Fan Zhu, Ying Tai, Ling Shao. Learning Multi-Granular Hypergraphs for Video-Based Person Re-Identification. In IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2020.

 

Lei Zhang, Jiangtao Nie, Wei Wei, Yanning Zhang, Shengcai Liao, and Ling Shao. Unsupervised Adaptation Learning for Hyperspectral Imagery Super-resolution. In IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2020.

 

Syed Waqas Zamir, Aditya Arora, Salman Khan, Munawar Hayat, Fahad Shahbaz Khan, Ming-Hsuan Yang and Ling Shao. CycleISP: Real Image Restoration via Improved Data Synthesis. In IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2020.

 

Jiale Cao, Hisham Cholakkal, Rao Muhammad Anwer, Fahad Shahbaz Khan, Yanwei Pang and Ling Shao. D2Det: Towards High Quality Object Detection and Instance Segmentation. In IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2020.

 

Muhammad Haris Khan, John McDonagh, Salman Khan, Muhammad Shahabuddin, Aditya Arora, Fahad Shahbaz Khan, Ling Shao and Georgios Tzimiropoulos. AnimalWeb: A Large-Scale Hierarchical Dataset of Annotated Animal Faces. In IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2020.

 

Xingping Dong, Jianbing Shen, Ling Shao, Fatih Porikli. CLNet: A Compact Latent Network for Fast Adjusting Siamese Trackers. In The 16th European Conference on Computer Vision (ECCV), 23-28 August, 2020.

 

Mang Ye, Jianbing Shen, David J. Crandall, Ling Shao, Jiebo Luo. Dynamic Dual-Attentive Aggregation Learning for VisibleInfrared Re-identification. In The 16th European Conference on Computer Vision (ECCV), 23-28 August, 2020.

 

Deng-Ping Fan, Yingjie Zhai, Ali Borji, Jufeng Yang, Ling Shao. BBS-Net: Rgb-d salient object detection with a bifurcated backbone strategy network. In The 16th European Conference on Computer Vision (ECCV), 23-28 August, 2020.

 

Lei Huang, Jie Qin, Li Liu, Fan Zhu, Ling Shao. Layer-wise Conditioning Analysis in Exploring the Learning Dynamics of DNNs. In The 16th European Conference on Computer Vision (ECCV), 23-28 August, 2020.

 

Guo-Sen Xie, Li Liu, Fan Zhu, Fang Zhao, Zheng Zhang, Yazhou Yao, Jie Qin, Ling Shao. Region Graph Embedding Network for Zero-Shot Learning. In The 16th European Conference on Computer Vision (ECCV), 23-28 August, 2020.

 

Yuming Shen, Jie Qin, Lei Huang, Li Liu, Fan Zhu, Ling Shao. Invertible Zero-Shot Recognition Flows. In The 16th European Conference on Computer Vision (ECCV), 23-28 August, 2020.

 

Jiaxin Chen, Jie Qin, Yuming Shen, Li Liu, Fan Zhu, Ling Shao. Learning Attentive and Hierarchical Representations for 3D Shape Recognition. In The 16th European Conference on Computer Vision (ECCV), 23-28 August, 2020.

 

Shengcai Liao, and Ling Shao. Interpretable and Generalizable Person Re-identiffication with Query-adaptive Convolution and Temporal Lifting. In The 16th European Conference on Computer Vision (ECCV), 23-28 August, 2020.

 

Fang Zhao, Shengcai Liao, Guosen Xie, Jian Zhao, Kaihao Zhang, and Ling Shao. Unsupervised Domain Adaptation with Noise Resistible Mutual-Training for Person Re-identiffication. In The 16th European Conference on Computer Vision (ECCV), 23-28 August, 2020.

 

Jiale Cao, Rao Muhammad Anwer, Hisham Cholakkal, Fahad Shahbaz Khan, Yanwei Pang and Ling Shao. SipMask: Spatial Information Preservation for Fast Image and Video Instance Segmentation. In The 16th European Conference on Computer Vision (ECCV), 23-28 August, 2020.

 

Sanath Narayan, Akshita Gupta, Fahad Shahbaz Khan, Cees Snoek, and Ling Shao. Latent Embedding Feedback and Discriminative Features for Zero-Shot Classification. In The 16th European Conference on Computer Vision (ECCV), 23-28 August, 2020.

 

Jin Xie, Hisham Cholakkal, Rao Muhammad Anwer, Fahad Shahbaz Khan, Yanwei Pang, Ling Shao and Mubarak Shah. Count- and Similarity-aware R-CNN for Pedestrian Detection. In The 16th European Conference on Computer Vision (ECCV), 23-28 August, 2020.

 

Syed Waqas Zamir, Aditya Arora, Salman Khan, Munawar Hayat, Fahad Shahbaz Khan, Ming-Hsuan Yang and Ling Shao. Learning Enriched Features for Real Image Restoration and Enhancement. In The 16th European Conference on Computer Vision (ECCV), 23-28 August, 2020.

 

J. Rajasegaran, M. Hayat, S. H. Khan, F. S. Khan, and L. Shao, Random Path Selection for Continual Learning, in Advances in Neural Information Processing Systems (NIPS), pp. 12648-12658, 2019.

 

Lizhong Ding, Mengyang Yu, Li Liu, Fan Zhu, Yong Liu, Yu Li, Ling Shao, Two Generator Game: Learning to Sample via Linear Goodness-of-Fit Test. in Advances in Neural Information Processing Systems (NIPS), pp. 12648-12658, 2019.

 

J. Li, S. Shang, and L. Shao, MetaNER: Named Entity Recognition with Meta-Learning, in The Web Conference (WWW), pp. 429-440, 2020.

 

 J. Chen, J. Qin, L. Liu, F. Zhu, F. Shen, J. Xie, and L. Shao, Deep Sketch-Shape Hashing With Segmented 3D Stochastic Viewing, in IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp. 791-800, 2019.

 

 L. Chen, S. Shang, C. S. Jensen, B. Yao, Z. Zhang, and L. Shao, Effective and Efficient Reuse of Past Travel Behavior for Route Recommendation, in ACM SIGKDD International Conference on Knowledge Discovery & Data Mining (KDD), pp. 488-498, 2019.

 

 H. Cholakkal, G. Sun, F. S. Khan, and L. Shao, Object Counting and Instance Segmentation With Image-Level Supervision, in IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp. 12397-12405, 2019.

 

 H. Dai and L. Shao, PointAE: Point Auto-Encoder for 3D Statistical Shape and Texture Modelling, in IEEE/CVF International Conference on Computer Vision (ICCV), pp. 5409-5418, 2019.

 

 D. Deng, C. Yang, S. Shang, F. Zhu, L. Liu, and L. Shao, LCJoin: Set Containment Join via List Crosscutting, in IEEE International Conference on Data Engineering (ICDE), pp. 362-373, 2019.

 

 L. Ding, M. Yu, L. Liu, F. Zhu, Y. Liu, Y. Li, and L. Shao, Two Generator Game: Learning to Sample via Linear Goodness-of-Fit Test, in Advances in Neural Information Processing Systems (NIPS), pp. 11257-11268, 2019.

 

 M. Hayat, S. H. Khan, S. W. Zamir, J. Shen, and L. Shao, Gaussian Affinity for Max-Margin Class Imbalanced Learning, in IEEE/CVF International Conference on Computer Vision (ICCV), pp. 6468-6478, 2019.

 

 L. Huang, Y. Zhou, F. Zhu, L. Liu, and L. Shao, Iterative Normalization: Beyond Standardization Towards Efficient Whitening, in IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp. 4874-4883, 2019.

 

 R. T. Ionescu, F. S. Khan, M.-I. Georgescu, and L. Shao, Object-Centric Auto-Encoders and Dummy Anomalies for Abnormal Event Detection in Video, in IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp. 7842-7851, 2019.

 

 X. Jiang, Z. Xiao, B. Zhang, X. Zhen, X. Cao, D. S. Doermann, and L. Shao, Crowd Counting and Density Estimation by Trellis Encoder-Decoder Networks, in IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp. 6133-6142, 2019.

 

 S. H. Khan, M. Hayat, S. W. Zamir, J. Shen, and L. Shao, Striking the Right Balance With Uncertainty, in IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp. 103-112, 2019.

 

 X. Lu, W. Wang, C. Ma, J. Shen, L. Shao, and F. Porikli, See More, Know More: Unsupervised Video Object Segmentation With Co-Attention Siamese Networks, in IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp. 3623-3632, 2019.

 

 D. Mandal, S. Narayan, S. K. Dwivedi, V. Gupta, S. Ahmed, F. S. Khan, and L. Shao, Out-Of-Distribution Detection for Generalized Zero-Shot Action Recognition, in IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp. 9985-9993, 2019.

 

 A. Mustafa, S. H. Khan, M. Hayat, R. Goecke, J. Shen, and L. Shao, Adversarial Defense by Restricting the Hidden Space of Deep Neural Networks, in IEEE/CVF International Conference on Computer Vision (ICCV), pp. 3384-3393, 2019.

 

 S. Narayan, H. Cholakkal, F. S. Khan, and L. Shao, 3C-Net: Category Count and Center Loss for Weakly-Supervised Action Localization, in IEEE/CVF International Conference on Computer Vision (ICCV), pp. 8678-8686, 2019.

 

 J. Nie, R. M. Anwer, H. Cholakkal, F. S. Khan, Y. Pang, and L. Shao, Enriched Feature Guided Refinement Network for Object Detection, in IEEE/CVF International Conference on Computer Vision (ICCV), pp. 9536-9545, 2019.

 

 Y. Pang, Y. Li, J. Shen, and L. Shao, Towards Bridging Semantic Gap to Improve Semantic Segmentation, in IEEE/CVF International Conference on Computer Vision (ICCV), pp. 4229-4238, 2019.

 

 Y. Pang, T. Wang, R. M. Anwer, F. S. Khan, and L. Shao, Efficient Featurized Image Pyramid Network for Single Shot Detector, in IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp. 7336-7344, 2019.

 

 Y. Pang, J. Xie, M. H. Khan, R. M. Anwer, F. S. Khan, and L. Shao, Mask-Guided Attention Network for Occluded Pedestrian Detection, in IEEE/CVF International Conference on Computer Vision (ICCV), pp. 4966-4974, 2019.

 

 Z. Shen, W. Wang, X. Lu, J. Shen, H. Ling, T. Xu, and L. Shao, Human-Aware Motion Deblurring, in IEEE/CVF International Conference on Computer Vision (ICCV), pp. 5571-5580, 2019.

 

 T. Wang, R. M. Anwer, H. Cholakkal, F. S. Khan, Y. Pang, and L. Shao, Learning Rich Features at High-Speed for Single-Shot Object Detection, in IEEE/CVF International Conference on Computer Vision (ICCV), pp. 1971-1980, 2019.

 

 T. Wang, R. M. Anwer, M. H. Khan, F. S. Khan, Y. Pang, L. Shao, and J. Laaksonen, Deep Contextual Attention for Human-Object Interaction Detection, in IEEE/CVF International Conference on Computer Vision (ICCV), pp. 5693-5701, 2019.

 

 W. Wang, X. Lu, J. Shen, D. Crandall, and L. Shao, Zero-Shot Video Object Segmentation via Attentive Graph Neural Networks, in IEEE/CVF International Conference on Computer Vision (ICCV), pp. 9235-9244, 2019.

 

 W. Wang, J. Shen, M.-M. Cheng, and L. Shao, An Iterative and Cooperative Top-Down and Bottom-Up Inference Network for Salient Object Detection, in IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp. 5968-5977, 2019.

 

 W. Wang, Z. Zhang, S. Qi, J. Shen, Y. Pang, and L. Shao, Learning Compositional Neural Information Fusion for Human Parsing, in IEEE/CVF International Conference on Computer Vision (ICCV), pp. 5702-5712, 2019.

 

 Z. Wang, J. Xu, L. Liu, F. Zhu, and L. Shao, RANet: Ranking Attention Network for Fast Video Object Segmentation, in IEEE/CVF International Conference on Computer Vision (ICCV), pp. 3977-3986, 2019.

 

 Z. Wei, J. Zhang, L. Liu, F. Zhu, F. Shen, Y. Zhou, S. Liu, Y. Sun, and L. Shao, Building Detail-Sensitive Semantic Segmentation Networks With Polynomial Pooling, in IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp. 7115-7123, 2019.

 

 G.-S. Xie, L. Liu, X. Jin, F. Zhu, Z. Zhang, J. Qin, Y. Yao, and L. Shao, Attentive Region Embedding Network for Zero-Shot Learning, in IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp. 9384-9393, 2019.

 

A. Zhang, J. Shen, Z. Xiao, F. Zhu, X. Zhen, X. Cao, and L. Shao, Relational Attention Network for Crowd Counting, in IEEE/CVF International Conference on Computer Vision (ICCV), pp. 6787-6796, 2019.

 

 A. Zhang, L. Yue, J. Shen, F. Zhu, X. Zhen, X. Cao, and L. Shao, Attentional Neural Fields for Crowd Counting, in IEEE/CVF International Conference on Computer Vision (ICCV), pp. 5713-5722, 2019.

 

 Y. Zhou, X. He, L. Huang, L. Liu, F. Zhu, S. Cui, and L. Shao, Collaborative Learning of Semi-Supervised Segmentation and Classification for Medical Images, in IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp. 2079-2088, 2019.

 

 X. Dong, J. Shen, W. Wang, Y. Liu, L. Shao, and F. Porikli, Hyperparameter Optimization for Tracking With Continuous Deep Q-Learning, in IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp. 518-527, 2018.

 

 G. Hu, L. Liu, Y. Yuan, Z. Yu, Y. Hua, Z. Zhang, F. Shen, L. Shao, T. M. Hospedales, N. M. Robertson, and Y. Yang, Deep Multi-task Learning to Recognise Subtle Facial Expressions of Mental States, in European Conference Computer Vision (ECCV), vol. 11216, pp. 106-123, 2018.

 

 Y. Shen, L. Liu, F. Shen, and L. Shao, Zero-Shot Sketch-Image Hashing, in IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp. 3598-3607, 2018.

 

 D. Wan, F. Shen, L. Liu, F. Zhu, J. Qin, L. Shao, and H. T. Shen, TBN: Convolutional Neural Network with Ternary Inputs and Binary Weights, in European Conference Computer Vision (ECCV), vol. 11206, pp. 322-339, 2018.

 

 J. Zhang, F. Shen, L. Liu, F. Zhu, M. Yu, L. Shao, H. T. Shen, and L. Van Gool, Generative Domain-Migration Hashing for Sketch-to-Image Retrieval, in European Conference Computer Vision (ECCV), vol. 11206, pp. 304-321, 2018.

 

 Z. Zhang, L. Liu, J. Qin, F. Zhu, F. Shen, Y. Xu, L. Shao, and H. T. Shen, Highly-Economized Multi-view Binary Compression for Scalable Image Clustering, in European Conference Computer Vision (ECCV), vol. 11216, pp. 731-748, 2018.

 

 Y. Zhou and L. Shao, Viewpoint-Aware Attentive Multi-View Inference for Vehicle Re-Identification, in IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp. 6489-6498, 2018.

 

 Y. Zhu, Y. Long, Y. Guan, S. D. Newsam, and L. Shao, Towards Universal Representation for Unseen Action Recognition, in IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp. 9436-9445, 2018.

 

 J. Chen, Y. Wang, J. Qin, L. Liu, and L. Shao, Fast Person Re-identification via Cross-Camera Semantic Binary Transformation, in IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp. 5330-5339, 2017.

 

 Y. Huang, L. Shao, and A. F. Frangi, Simultaneous Super-Resolution and Cross-Modality Synthesis of 3D Medical Images Using Weakly-Supervised Joint Convolutional Sparse Coding, in IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp. 5787-5796, 2017.

 

 L. Liu, L. Shao, F. Shen, and M. Yu, Discretely Coding Semantic Rank Orders for Supervised Image Hashing, in IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp. 5140-5149, 2017.

 

 L. Liu, F. Shen, Y. Shen, X. Liu, and L. Shao, Deep Sketch Hashing: Fast Free-Hand Sketch-Based Image Retrieval, in IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp. 2298-2307, 2017.

 

 Y. Long, L. Liu, L. Shao, F. Shen, G. Ding, and J. Han, From Zero-Shot Learning to Conventional Supervised Classification: Unseen Visual Data Synthesis, in IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp. 6165-6174, 2017.

 

 J. Qin, L. Liu, L. Shao, B. Ni, C. Chen, F. Shen, and Y. Wang, Binary Coding for Partial Action Analysis with Limited Observation Ratios, in IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp. 6728-6737, 2017.

 

 J. Qin, L. Liu, L. Shao, F. Shen, B. Ni, J. Chen, and Y. Wang, Zero-Shot Action Recognition with Error-Correcting Output Codes, in IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp. 1042-1051, 2017.

 

 Y. Shen, L. Liu, L. Shao, and J. Song, Deep Binaries: Encoding Semantic-Rich Cues for Efficient Textual-Visual Cross Retrieval, in IEEE International Conference on Computer Vision (ICCV), pp. 4117-4126, 2017.

 

 Y. Zhou, L. Liu, L. Shao, and M. Mellor, DAVE: A Unified Framework for Fast Vehicle Detection and Annotation, in European Conference Computer Vision (ECCV), vol. 9906, pp. 278-293, 2016.

 

 L. Liu, M. Yu, and L. Shao, Projection Bank: From High-Dimensional Data to Medium-Length Binary Codes, in IEEE International Conference on Computer Vision (ICCV), pp. 2821-2829, 2015.

 

 S. Jones and L. Shao, A Multigraph Representation for Improved Unsupervised/Semi-supervised Learning of Human Actions, in IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp. 820-826, 2014.

 

 S. Jones and L. Shao, Unsupervised Spectral Dual Assignment Clustering of Human Actions in Context, in IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp. 604-611, 2014.

 

 D. Wu and L. Shao, Deep Dynamic Neural Networks for Gesture Segmentation and Recognition, in European Conference Computer Vision (ECCV), vol. 8925, pp. 552-571, 2014.

 

 D. Wu and L. Shao, Leveraging Hierarchical Parametric Networks for Skeletal Joints Based Action Segmentation and Recognition, in IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp. 724-731, 2014.

 

F. Zhu, Z. Jiang, and L. Shao, Submodular Object Recognition, in IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp. 2457-2464, 2014.