HRNet (CVPR'2019)
```bibtex
@inproceedings{sun2019deep,
title={Deep high-resolution representation learning for human pose estimation},
author={Sun, Ke and Xiao, Bin and Liu, Dong and Wang, Jingdong},
booktitle={Proceedings of the IEEE conference on computer vision and pattern recognition},
pages={5693--5703},
year={2019}
}
```
DarkPose (CVPR'2020)
```bibtex
@inproceedings{zhang2020distribution,
title={Distribution-aware coordinate representation for human pose estimation},
author={Zhang, Feng and Zhu, Xiatian and Dai, Hanbin and Ye, Mao and Zhu, Ce},
booktitle={Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition},
pages={7093--7102},
year={2020}
}
```
COCO-WholeBody (ECCV'2020)
```bibtex
@inproceedings{jin2020whole,
title={Whole-Body Human Pose Estimation in the Wild},
author={Jin, Sheng and Xu, Lumin and Xu, Jin and Wang, Can and Liu, Wentao and Qian, Chen and Ouyang, Wanli and Luo, Ping},
booktitle={Proceedings of the European Conference on Computer Vision (ECCV)},
year={2020}
}
```
Results on COCO-WholeBody v1.0 val with detector having human AP of 56.4 on COCO val2017 dataset
| Arch | Input Size | Body AP | Body AR | Foot AP | Foot AR | Face AP | Face AR | Hand AP | Hand AR | Whole AP | Whole AR | ckpt | log |
| :-------------------------------------- | :--------: | :-----: | :-----: | :-----: | :-----: | :-----: | :-----: | :-----: | :-----: | :------: | :------: | :--------------------------------------: | :-------------------------------------: |
| [pose_hrnet_w32_dark](/configs/wholebody_2d_keypoint/topdown_heatmap/coco-wholebody/td-hm_hrnet-w32_dark-8xb64-210e_coco-wholebody-256x192.py) | 256x192 | 0.693 | 0.764 | 0.564 | 0.674 | 0.737 | 0.809 | 0.503 | 0.602 | 0.582 | 0.671 | [ckpt](https://download.openmmlab.com/mmpose/top_down/hrnet/hrnet_w32_coco_wholebody_256x192_dark-469327ef_20200922.pth) | [log](https://download.openmmlab.com/mmpose/top_down/hrnet/hrnet_w32_coco_wholebody_256x192_dark_20200922.log.json) |
| [pose_hrnet_w48_dark+](/configs/wholebody_2d_keypoint/topdown_heatmap/coco-wholebody/td-hm_hrnet-w48_dark-8xb32-210e_coco-wholebody-384x288.py) | 384x288 | 0.742 | 0.807 | 0.707 | 0.806 | 0.841 | 0.892 | 0.602 | 0.694 | 0.661 | 0.743 | [ckpt](https://download.openmmlab.com/mmpose/top_down/hrnet/hrnet_w48_coco_wholebody_384x288_dark-f5726563_20200918.pth) | [log](https://download.openmmlab.com/mmpose/top_down/hrnet/hrnet_w48_coco_wholebody_384x288_dark_20200918.log.json) |
Note: `+` means the model is first pre-trained on original COCO dataset, and then fine-tuned on COCO-WholeBody dataset. We find this will lead to better performance.