Ranking - 3D Reconstruction - All Frames
Method | Time | Description | 3D Joints Translation Error | 3D Joints MPJPE | 3D Joints MPJPE-PA | GHUM MPVPE | GHUM MPVPE-PA | SMPLX MPVPE | SMPLX MPVPE-PA |
---|---|---|---|---|---|---|---|---|---|
Cliff | 06/08/2023 - 15:17 |
@inproceedings{li2022cliff, title={Cliff: Carrying location information in full frames into human pose and shape estimation}, author={Li, Zhihao and Liu, Jianzhuang and Zhang, Zhensong and Xu, Songcen and Yan, Youliang}, booktitle={Computer Vision--ECCV 2022: 17th European Conference, Tel Aviv, Israel, October 23--27, 2022, Proceedings, Part V}, pages={590--606}, year={2022}, organization={Springer} } |
896.49 | 105.42 | 55.17 | 108.85 | 54.97 | 107.73 | 51.54 |
CRMH | 06/08/2023 - 15:13 |
@inproceedings{jiang2020coherent, title={Coherent reconstruction of multiple humans from a single image}, author={Jiang, Wen and Kolotouros, Nikos and Pavlakos, Georgios and Zhou, Xiaowei and Daniilidis, Kostas}, booktitle={Proceedings of the IEEE/CVF conference on computer vision and pattern recognition}, pages={5579--5588}, year={2020} } |
3283.89 | 116.19 | 62.41 | 126.10 | 65.89 | 120.12 | 59.86 |
REMIPS | 06/10/2023 - 16:47 |
This is a weakly-supervised method. No 3d ground truth data (joints, rotation angles, vertices) was used in training. The CHI3D training subset is not used in any form to train this method. PDF: https://proceedings.neurips.cc/paper/2021/file/a1a2c3fed88e9b3ba5bc3625c074a04e-Paper.pdf @article{fieraru2021remips, title={REMIPS: Physically consistent 3d reconstruction of multiple interacting people under weak supervision}, author={Fieraru, Mihai and Zanfir, Mihai and Szente, Teodor and Bazavan, Eduard and Olaru, Vlad and Sminchisescu, Cristian}, journal={Advances in Neural Information Processing Systems}, volume={34}, pages={19385--19397}, year={2021} } |
667.01 | 119.45 | 67.51 | 122.00 | 68.08 | 112.53 | 58.68 |