| Hydraplus-net: Attentive deep features for pedestrian analysis X Liu, H Zhao, M Tian, L Sheng, J Shao, S Yi, J Yan, X Wang IEEE International Conference on Computer Vision (ICCV), 2017, 2017 | 349 | 2017 |
| Optical Flow Guided Feature: A Fast and Robust Motion Representation for Video Action Recognition S Sun, Z Kuang, W Ouyang, L Sheng, W Zhang Computer Vision and Pattern Recognition (CVPR), 2018 IEEE Conference on, 2018 | 191 | 2018 |
| GS3D: An Efficient 3D Object Detection Framework for Autonomous Driving B Li, W Ouyang, L Sheng, X Zeng, X Wang Computer Vision and Pattern Recognition (CVPR), 2019 IEEE Conference on, 2019 | 143 | 2019 |
| Avatar-Net: Multi-scale Zero-shot Style Transfer by Feature Decoration L Sheng, Z Lin, J Shao, X Wang Computer Vision and Pattern Recognition (CVPR), 2018 IEEE Conference on, 2018 | 122 | 2018 |
| Exploring Disentangled Feature Representation Beyond Face Identification Y Liu, F Wei, J Shao, L Sheng, Y Junjie, W Xiaogang Computer Vision and Pattern Recognition (CVPR), 2018 IEEE Conference on, 2018 | 103 | 2018 |
| Zoom-net: Mining deep feature interactions for visual relationship recognition G Yin, L Sheng, B Liu, N Yu, X Wang, J Shao, CC Loy Proceedings of the European Conference on Computer Vision (ECCV), 322-338, 2018 | 98 | 2018 |
| Camp: Cross-modal adaptive message passing for text-image retrieval Z Wang, X Liu, H Li, L Sheng, J Yan, X Wang, J Shao Proceedings of the IEEE/CVF International Conference on Computer Vision …, 2019 | 73 | 2019 |
| Morphing and sampling network for dense point cloud completion M Liu, L Sheng, S Yang, J Shao, SM Hu Thirty-Fourth AAAI Conference on Artifical Intelligence, 2020 | 70 | 2020 |
| Semantics Disentangling for Text-to-Image Generation G Yin, B Liu, L Sheng, N Yu, X Wang, J Shao Computer Vision and Pattern Recognition (CVPR), 2019 IEEE Conference on, 2019 | 68 | 2019 |
| Multi-label image classification via knowledge distillation from weakly-supervised detection Y Liu, L Sheng, J Shao, J Yan, S Xiang, C Pan Proceedings of the 26th ACM international conference on Multimedia, 700-708, 2018 | 52 | 2018 |
| Video Generation from Single Semantic Label Map J Pan, C Wang, X Jia, J Shao, L Sheng, J Yan, X Wang Computer Vision and Pattern Recognition (CVPR), 2019 IEEE Conference on, 2019 | 44 | 2019 |
| Thinking in frequency: Face forgery detection by mining frequency-aware clues Y Qian, G Yin, L Sheng, Z Chen, J Shao European Conference on Computer Vision, 86-103, 2020 | 43 | 2020 |
| Real-time head pose tracking with online face template reconstruction S Li, KN Ngan, R Paramesran, L Sheng IEEE transactions on pattern analysis and machine intelligence 38 (9), 1922-1928, 2015 | 38 | 2015 |
| Improving pedestrian attribute recognition with weakly-supervised multi-scale attribute-specific localization C Tang, L Sheng, Z Zhang, X Hu Proceedings of the IEEE/CVF International Conference on Computer Vision …, 2019 | 30 | 2019 |
| Unsupervised collaborative learning of keyframe detection and visual odometry towards monocular deep slam L Sheng, D Xu, W Ouyang, X Wang Proceedings of the IEEE/CVF International Conference on Computer Vision …, 2019 | 23 | 2019 |
| Context and Attribute Grounded Dense Captioning G Yin, L Sheng, B Liu, N Yu, X Wang, J Shao Computer Vision and Pattern Recognition (CVPR), 2019 IEEE Conference on, 2019 | 21 | 2019 |
| A Head Pose Tracking System Using RGB-D Camera S Li, KN Ngan, L Sheng The 9th International Conference on Computer Vision Systems, 2013, 2013 | 21 | 2013 |
| A Generative Model for Depth-based Robust 3D Facial Pose Tracking L Sheng, J Cai, TJ Cham, V Pavlovic, KN Ngan Computer Vision and Pattern Recognition (CVPR), 2017 IEEE Conference on, 2017 | 12 | 2017 |
| Online Temporally Consistent Indoor Depth Video Enhancement via Static Structure L Sheng, KN Ngan, CL Lim, S Li IEEE Transaction on Image Processing, 2015 | 12 | 2015 |
| Depth Enhancement Based on Hybrid Geometric Hole Filling Strategy L Sheng, KN Ngan, S Li IEEE International Conference on Image Processing, 2013, 2013 | 9 | 2013 |
Jing ShaoResearch Director, SenseTime Group LTD在 sensetime.com 的电子邮件经过验证
