| Whole-body human pose estimation in the wild S Jin, L Xu, J Xu, C Wang, W Liu, C Qian, W Ouyang, P Luo Computer Vision–ECCV 2020: 16th European Conference, Glasgow, UK, August 23 …, 2020 | 196 | 2020 |
| Human pose regression with residual log-likelihood estimation J Li, S Bian, A Zeng, C Wang, B Pang, W Liu, C Lu Proceedings of the IEEE/CVF international conference on computer vision …, 2021 | 159 | 2021 |
| Weakly-supervised discovery of geometry-aware representation for 3d human pose estimation X Chen, KY Lin, W Liu, C Qian, L Lin Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2019 | 131 | 2019 |
| Differentiable hierarchical graph grouping for multi-person pose estimation S Jin, W Liu, E Xie, W Wang, C Qian, W Ouyang, P Luo Computer Vision–ECCV 2020: 16th European Conference, Glasgow, UK, August 23 …, 2020 | 128 | 2020 |
| 3d human mesh regression with dense correspondence W Zeng, W Ouyang, P Luo, W Liu, X Wang Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2020 | 101 | 2020 |
| Omni-sourced webly-supervised learning for video recognition H Duan, Y Zhao, Y Xiong, W Liu, D Lin European conference on computer vision, 670-688, 2020 | 96 | 2020 |
| Smap: Single-shot multi-person absolute 3d pose estimation J Zhen, Q Fang, J Sun, W Liu, W Jiang, H Bao, X Zhou Computer Vision–ECCV 2020: 16th European Conference, Glasgow, UK, August 23 …, 2020 | 93 | 2020 |
| Not all tokens are equal: Human-centric visual analysis via token clustering transformer W Zeng, S Jin, W Liu, C Qian, P Luo, W Ouyang, X Wang Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2022 | 87 | 2022 |
| Multi-person articulated tracking with spatial and temporal embeddings S Jin, W Liu, W Ouyang, C Qian Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2019 | 76 | 2019 |
| Person search in videos with one portrait through visual and temporal links Q Huang, W Liu, D Lin Proceedings of the European conference on computer vision (ECCV), 425-441, 2018 | 73 | 2018 |
| Drpose3d: Depth ranking in 3d human pose estimation M Wang, X Chen, W Liu, C Qian, L Lin, L Ma arXiv preprint arXiv:1805.08973, 2018 | 64 | 2018 |
| When human pose estimation meets robustness: Adversarial algorithms and benchmarks J Wang, S Jin, W Liu, W Liu, C Qian, P Luo Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2021 | 60 | 2021 |
| Towards multi-person pose tracking: Bottom-up and top-down methods S Jin, X Ma, Z Han, Y Wu, W Yang, W Liu, C Qian, W Ouyang ICCV Posetrack workshop 2 (3), 7, 2017 | 57 | 2017 |
| Vipnas: Efficient video pose estimation via neural architecture search L Xu, Y Guan, S Jin, W Liu, C Qian, P Luo, W Ouyang, X Wang Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2021 | 55 | 2021 |
| Hmor: Hierarchical multi-person ordinal relations for monocular multi-person 3d pose estimation C Wang, J Li, W Liu, C Qian, C Lu Computer Vision–ECCV 2020: 16th European Conference, Glasgow, UK, August 23 …, 2020 | 53 | 2020 |
| A cascaded inception of inception network with attention modulated feature fusion for human pose estimation W Liu, J Chen, C Li, C Qian, X Chu, X Hu Proceedings of the AAAI Conference on Artificial Intelligence 32 (1), 2018 | 44 | 2018 |
| Aligning bag of regions for open-vocabulary object detection S Wu, W Zhang, S Jin, W Liu, CC Loy Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2023 | 41 | 2023 |
| Graph-based 3d multi-person pose estimation using multi-view images S Wu, S Jin, W Liu, L Bai, C Qian, D Liu, W Ouyang Proceedings of the IEEE/CVF international conference on computer vision …, 2021 | 37 | 2021 |
| 3d interacting hand pose estimation by hand de-occlusion and removal H Meng, S Jin, W Liu, C Qian, M Lin, W Ouyang, P Luo European Conference on Computer Vision, 380-397, 2022 | 25 | 2022 |
| Hmor: Hierarchical multi-person ordinal relations for monocular multi-person 3d pose estimation J Li, C Wang, W Liu, C Qian, C Lu arXiv preprint arXiv:2008.00206, 2020 | 23 | 2020 |
Chen QianSenseTime在 sensetime.com 的电子邮件经过验证
