Poi: Multiple object tracking with high performance detection and appearance feature F Yu, W Li, Q Li, Y Liu, X Shi, J Yan Computer Vision–ECCV 2016 Workshops: Amsterdam, The Netherlands, October 8 …, 2016 | 543 | 2016 |
Grid r-cnn X Lu, B Li, Y Yue, Q Li, J Yan Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2019 | 467 | 2019 |
Equalization loss for long-tailed object recognition J Tan, C Wang, B Li, Q Li, W Ouyang, C Yin, J Yan Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2020 | 451 | 2020 |
Mimicking very efficient network for object detection Q Li, S Jin, J Yan Proceedings of the ieee conference on computer vision and pattern …, 2017 | 352 | 2017 |
Dmcp: Differentiable markov channel pruning for neural networks S Guo, Y Wang, Q Li, J Yan Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2020 | 165 | 2020 |
Jointly learning deep features, deformable parts, occlusion and classification for pedestrian detection W Ouyang, H Zhou, H Li, Q Li, J Yan, X Wang IEEE transactions on pattern analysis and machine intelligence 40 (8), 1874-1887, 2017 | 154 | 2017 |
Equalization loss v2: A new gradient balance approach for long-tailed object detection J Tan, X Lu, G Zhang, C Yin, Q Li Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2021 | 153 | 2021 |
Refinemask: Towards high-quality instance segmentation with fine-grained features G Zhang, X Lu, J Tan, J Li, Z Zhang, Q Li, X Hu Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2021 | 109 | 2021 |
Mimicdet: Bridging the gap between one-stage and two-stage object detection X Lu, Q Li, B Li, J Yan Computer Vision–ECCV 2020: 16th European Conference, Glasgow, UK, August 23 …, 2020 | 76 | 2020 |
Wider face and pedestrian challenge 2018: Methods and results CC Loy, D Lin, W Ouyang, Y Xiong, S Yang, Q Huang, D Zhou, W Xia, ... arXiv preprint arXiv:1902.06854, 2019 | 44 | 2019 |
Residual knowledge distillation M Gao, Y Shen, Q Li, CC Loy arXiv preprint arXiv:2002.09168, 2020 | 37 | 2020 |
An embarrassingly simple approach for knowledge distillation M Gao, Y Shen, Q Li, J Yan, L Wan, D Lin, CC Loy, X Tang arXiv preprint arXiv:1812.01819, 2018 | 24 | 2018 |
1st place solution of lvis challenge 2020: A good box is not a guarantee of a good mask J Tan, G Zhang, H Deng, C Wang, L Lu, Q Li, J Dai arXiv preprint arXiv:2009.01559, 2020 | 16 | 2020 |
Methods and apparatuses for object detection, and devices L Liu, Q Li, J Yan US Patent 11,222,441, 2022 | 5 | 2022 |
Differentiable dynamic wirings for neural networks K Yuan, Q Li, S Guo, D Chen, A Zhou, F Yu, Z Liu Proceedings of the IEEE/CVF International Conference on Computer Vision, 327-336, 2021 | 5 | 2021 |
Grid r-cnn plus: Faster and better X Lu, B Li, Y Yue, Q Li, J Yan arXiv preprint arXiv:1906.05688, 2019 | 5 | 2019 |
Fixing the teacher-student knowledge discrepancy in distillation J Han, M Gao, Y Wang, Q Li, H Li, X Wang arXiv preprint arXiv:2103.16844, 2021 | 3 | 2021 |
Learning connectivity of neural networks from a topological perspective K Yuan, Q Li, J Shao, J Yan European Conference on Computer Vision, 737-753, 2020 | 3 | 2020 |
Methods and apparatuses for determining bounding box of target object, media, and devices LI Buyu, Q Li, J Yan US Patent 11,348,275, 2022 | 2 | 2022 |
Equalization loss for large vocabulary instance segmentation J Tan, C Wang, Q Li, J Yan arXiv preprint arXiv:1911.04692, 2019 | 2 | 2019 |