| Towards real-time multi-object tracking Z Wang, L Zheng, Y Liu, Y Li, S Wang European conference on computer vision, 107-122, 2020 | 955 | 2020 |
| Perceive where to focus: Learning visibility-aware part-level features for partial person re-identification Y Sun, Q Xu, Y Li, C Zhang, Y Li, S Wang, J Sun Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2019 | 398 | 2019 |
| A survey of recent advances in visual feature detection Y Li, S Wang, Q Tian, X Ding Neurocomputing 149, 736-751, 2015 | 277 | 2015 |
| Weakly supervised object localization with progressive domain adaptation D Li, JB Huang, Y Li, S Wang, MH Yang Proceedings of the IEEE conference on computer vision and pattern …, 2016 | 241 | 2016 |
| Linkage based face clustering via graph convolution network Z Wang, L Zheng, Y Li, S Wang Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2019 | 214 | 2019 |
| Video super-resolution with temporal group attention T Isobe, S Li, X Jia, S Yuan, G Slabaugh, C Xu, YL Li, S Wang, Q Tian Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2020 | 180 | 2020 |
| Visdrone-det2018: The vision meets drone object detection in image challenge results P Zhu, L Wen, D Du, X Bian, H Ling, Q Hu, Q Nie, H Cheng, C Liu, X Liu, ... Proceedings of the European Conference on Computer Vision (ECCV) Workshops, 0-0, 2018 | 150 | 2018 |
| Feature representation for statistical-learning-based object detection: A review Y Li, S Wang, Q Tian, X Ding Pattern Recognition 48 (11), 3542-3559, 2015 | 107 | 2015 |
| Learning part-based convolutional features for person re-identification Y Sun, L Zheng, Y Li, Y Yang, Q Tian, S Wang IEEE transactions on pattern analysis and machine intelligence 43 (3), 902-917, 2019 | 101 | 2019 |
| Cycas: Self-supervised cycle association for learning re-identifiable descriptions Z Wang, J Zhang, L Zheng, Y Liu, Y Sun, Y Li, S Wang Computer Vision–ECCV 2020: 16th European Conference, Glasgow, UK, August 23 …, 2020 | 96 | 2020 |
| Do different tracking tasks require different appearance models? Z Wang, H Zhao, YL Li, S Wang, P Torr, L Bertinetto Advances in neural information processing systems 34, 726-738, 2021 | 72 | 2021 |
| Data-uncertainty guided multi-phase learning for semi-supervised object detection Z Wang, Y Li, Y Guo, L Fang, S Wang Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2021 | 70 | 2021 |
| A2-FPN: Attention aggregation based feature pyramid network for instance segmentation M Hu, Y Li, L Fang, S Wang Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2021 | 66 | 2021 |
| Exploiting effective facial patches for robust gender recognition J Cheng, Y Li, J Wang, L Yu, S Wang Tsinghua Science and Technology 24 (3), 333-345, 2019 | 65 | 2019 |
| Person-independent head pose estimation based on random forest regression Y Li, S Wang, X Ding 2010 IEEE International Conference on Image Processing, 1521-1524, 2010 | 57 | 2010 |
| Intention oriented image captions with guiding objects Y Zheng, Y Li, S Wang Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2019 | 54 | 2019 |
| Detecting everything in the open world: Towards universal object detection Z Wang, Y Li, X Chen, SN Lim, A Torralba, H Zhao, S Wang Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2023 | 41 | 2023 |
| Delving into probabilistic uncertainty for unsupervised domain adaptive person re-identification J Han, YL Li, S Wang Proceedings of the AAAI conference on artificial intelligence 36 (1), 790-798, 2022 | 39 | 2022 |
| HAR-Net: Joint learning of hybrid attention for single-stage object detection YL Li, S Wang IEEE Transactions on Image Processing 29, 3092-3103, 2020 | 39 | 2020 |
| Softmax dissection: Towards understanding intra-and inter-class objective for embedding learning L He, Z Wang, Y Li, S Wang Proceedings of the AAAI conference on artificial intelligence 34 (07), 10957 …, 2020 | 32 | 2020 |
Shengjin WangTsinghua UniversityDirección de correo verificada de tsinghua.edu.cn
