Track to detect and segment: An online multi-object tracker J Wu, J Cao, L Song, Y Wang, M Yang, J Yuan Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2021 | 314 | 2021 |
SipMask: Spatial Information Preservation for Fast Image and Video Instance Segmentation J Cao, RM Anwer, H Cholakkal, FS Khan, Y Pang, L Shao Proceedings of European Conference on Computer Vision, 2020 | 198 | 2020 |
D2Det: Towards High Quality Object Detection and Instance Segmentation J Cao, H Cholakkal, RM Anwer, FS Khan, Y Pang, L Shao Proceedings of the IEEE Conference on Computer Vision and Pattern …, 2020 | 189 | 2020 |
Learning multilayer channel features for pedestrian detection J Cao, Y Pang, X Li IEEE Transactions on Image Processing 26 (7), 3210-3220, 2017 | 130 | 2017 |
Pedestrian detection inspired by appearance constancy and shape symmetry J Cao, Y Pang, X Li Proceedings of the IEEE Conference on Computer Vision and Pattern …, 2016 | 95 | 2016 |
Pedestrian detection inspired by appearance constancy and shape symmetry J Cao, Y Pang, X Li IEEE Transactions on Image Processing 25 (12), 5538-5551, 2016 | 95 | 2016 |
Hierarchical shot detector J Cao, Y Pang, J Han, X Li Proceedings of the IEEE/CVF International Conference on Computer Vision …, 2019 | 91 | 2019 |
From handcrafted to deep features for pedestrian detection: A survey J Cao, Y Pang, J Xie, FS Khan, L Shao IEEE Transactions on Pattern Analysis and Machine Intelligence 44 (9), 4913-4934, 2022 | 90 | 2022 |
JCS-Net: Joint classification and super-resolution network for small-scale pedestrian detection in surveillance images Y Pang, J Cao, J Wang, J Han IEEE Transactions on Information Forensics and Security 14 (12), 3322-3331, 2019 | 89 | 2019 |
High-level semantic networks for multi-scale object detection J Cao, Y Pang, S Zhao, X Li IEEE Transactions on Circuits and Systems for Video Technology 30 (10), 3372 …, 2020 | 75* | 2020 |
Triply Supervised Decoder Networks for Joint Detection and Segmentation J Cao, Y Pang, X Li Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2019 | 71 | 2019 |
TJU-DHD: A Diverse High-Resolution Dataset for Object Detection Y Pang, J Cao, Y Li, J Xie, H Sun, J Gong IEEE Transactions on Image Processing 30, 207-219, 2021 | 64 | 2021 |
Taking a look at small-scale pedestrians and occluded pedestrians J Cao, Y Pang, J Han, B Gao, X Li IEEE Transactions on Image Processing 29, 3143-3152, 2019 | 45 | 2019 |
Learning sampling distributions for efficient object detection Y Pang, J Cao, X Li IEEE Transactions on Cybernetics 47 (1), 117-129, 2016 | 44 | 2016 |
Randomly translational activation inspired by the input distributions of ReLU J Cao, Y Pang, X Li, J Liang Neurocomputing 275, 859-868, 2018 | 40 | 2018 |
Pstr: End-to-end one-step person search with transformers J Cao, Y Pang, RM Anwer, H Cholakkal, J Xie, M Shah, FS Khan Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2022 | 37 | 2022 |
Co-mining: Self-Supervised Learning for Sparsely Annotated Object Detection T Wang, T Yang, J Cao, X Zhang AAAI Conference on Artificial Intelligence (AAAI), 2020 | 37 | 2020 |
NETNet: Neighbor Erasing and Transferring Network for Better Single Shot Object Detection Y Li, Y Pang, J Shen, J Cao, L Shao Proceedings of the IEEE Conference on Computer Vision and Pattern …, 2020 | 37 | 2020 |
Cascade learning by optimally partitioning Y Pang, J Cao, X Li IEEE Transactions on Cybernetics 47 (12), 4148-4161, 2016 | 33 | 2016 |
3D vision with transformers: A survey J Lahoud, J Cao, FS Khan, H Cholakkal, RM Anwer, S Khan, MH Yang arXiv preprint arXiv:2208.04309, 2022 | 22 | 2022 |