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}
}
```
CrowdPose (CVPR'2019)
```bibtex
@article{li2018crowdpose,
title={CrowdPose: Efficient Crowded Scenes Pose Estimation and A New Benchmark},
author={Li, Jiefeng and Wang, Can and Zhu, Hao and Mao, Yihuan and Fang, Hao-Shu and Lu, Cewu},
journal={arXiv preprint arXiv:1812.00324},
year={2018}
}
```
Results on CrowdPose test with [YOLOv3](https://github.com/eriklindernoren/PyTorch-YOLOv3) human detector
| Arch | Input Size | AP | AP50 | AP75 | AP (E) | AP (M) | AP (H) | ckpt | log |
| :--------------------------------------------- | :--------: | :---: | :-------------: | :-------------: | :----: | :----: | :----: | :--------------------------------------------: | :-------------------------------------------: |
| [pose_hrnet_w32](/configs/body_2d_keypoint/topdown_heatmap/crowdpose/td-hm_hrnet-w32_8xb64-210e_crowdpose-256x192.py) | 256x192 | 0.675 | 0.825 | 0.729 | 0.770 | 0.687 | 0.553 | [ckpt](https://download.openmmlab.com/mmpose/top_down/hrnet/hrnet_w32_crowdpose_256x192-960be101_20201227.pth) | [log](https://download.openmmlab.com/mmpose/top_down/hrnet/hrnet_w32_crowdpose_256x192_20201227.log.json) |