CEO and Chief
Scientist of IIAI
Ling Shao was the Founding CEO and Chief
Scientist of the Inception Institute of
Artificial Intelligence (IIAI), Abu Dhabi, UAE. He was also 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 500 papers in top conferences/journals such as CVPR,
ICCV, ECCV, NeurIPS, ICML, ICLR, TPAMI and IJCV and over 30 US/EU 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 (Clarivate) for 6 consecutive years in
2018-2023. 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.
Awarded the Mohammed
bin Rashid Medal for Scientific Distinguishment (the highest scientific recognition
in the UAE).
Elected as a member
of the Mohammed bin Rashid Academy of Scientists (the National Academy of the
UAE).
Elected as a Fellow
of the IEEE.
CEO and
Chief Scientist,
Inception Institute of Artificial Intelligence (IIAI), Abu Dhabi, UAE, Jan. 2018-Dec.
2021
Provost and
Executive Vice President, Mohamed bin Zayed University of Artificial Intelligence, UAE, 2019-2021
Chair
Professor,
University of East Anglia, UK, 2016-2018
Chair
Professor,
Northumbria University, UK, 2014-2016
Senior
Lecturer, University
of Sheffield, UK, 2009-2014
Senior
Scientist, Philips
Research, the Netherlands, 2005-2009
Senior
Engineer, Queen's
University of Belfast, UK, 2005-2005
Ph.D., University
of Oxford
M.Sc. (by
research), University of Oxford
B.Eng., University
of Science and Technology of China
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
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