SimpleBaseline2D (ECCV'2018)
```bibtex
@inproceedings{xiao2018simple,
title={Simple baselines for human pose estimation and tracking},
author={Xiao, Bin and Wu, Haiping and Wei, Yichen},
booktitle={Proceedings of the European conference on computer vision (ECCV)},
pages={466--481},
year={2018}
}
```
Swin (ICCV'2021)
```bibtex
@inproceedings{liu2021swin,
title={Swin transformer: Hierarchical vision transformer using shifted windows},
author={Liu, Ze and Lin, Yutong and Cao, Yue and Hu, Han and Wei, Yixuan and Zhang, Zheng and Lin, Stephen and Guo, Baining},
booktitle={Proceedings of the IEEE/CVF International Conference on Computer Vision},
pages={10012--10022},
year={2021}
}
```
FPN (CVPR'2017)
```bibtex
@inproceedings{lin2017feature,
title={Feature pyramid networks for object detection},
author={Lin, Tsung-Yi and Doll{\'a}r, Piotr and Girshick, Ross and He, Kaiming and Hariharan, Bharath and Belongie, Serge},
booktitle={Proceedings of the IEEE conference on computer vision and pattern recognition},
pages={2117--2125},
year={2017}
}
```
COCO (ECCV'2014)
```bibtex
@inproceedings{lin2014microsoft,
title={Microsoft coco: Common objects in context},
author={Lin, Tsung-Yi and Maire, Michael and Belongie, Serge and Hays, James and Perona, Pietro and Ramanan, Deva and Doll{\'a}r, Piotr and Zitnick, C Lawrence},
booktitle={European conference on computer vision},
pages={740--755},
year={2014},
organization={Springer}
}
```
Results on COCO val2017 with detector having human AP of 56.4 on COCO val2017 dataset
| Arch | Input Size | AP | AP50 | AP75 | AR | AR50 | ckpt | log |
| :-------------------------------------------- | :--------: | :---: | :-------------: | :-------------: | :---: | :-------------: | :-------------------------------------------: | :-------------------------------------------: |
| [pose_swin_t](/configs/body_2d_keypoint/topdown_heatmap/coco/td-hm_swin-t-p4-w7_8xb32-210e_coco-256x192.py) | 256x192 | 0.724 | 0.901 | 0.806 | 0.782 | 0.940 | [ckpt](https://download.openmmlab.com/mmpose/top_down/swin/swin_t_p4_w7_coco_256x192-eaefe010_20220503.pth) | [log](https://download.openmmlab.com/mmpose/top_down/swin/swin_t_p4_w7_coco_256x192_20220503.log.json) |
| [pose_swin_b](/configs/body_2d_keypoint/topdown_heatmap/coco/td-hm_swin-b-p4-w7_8xb32-210e_coco-256x192.py) | 256x192 | 0.737 | 0.904 | 0.820 | 0.794 | 0.942 | [ckpt](https://download.openmmlab.com/mmpose/top_down/swin/swin_b_p4_w7_coco_256x192-7432be9e_20220705.pth) | [log](https://download.openmmlab.com/mmpose/top_down/swin/swin_b_p4_w7_coco_256x192_20220705.log.json) |
| [pose_swin_b](/configs/body_2d_keypoint/topdown_heatmap/coco/td-hm_swin-b-p4-w7_8xb32-210e_coco-384x288.py) | 384x288 | 0.759 | 0.910 | 0.832 | 0.811 | 0.946 | [ckpt](https://download.openmmlab.com/mmpose/top_down/swin/swin_b_p4_w7_coco_384x288-3abf54f9_20220705.pth) | [log](https://download.openmmlab.com/mmpose/top_down/swin/swin_b_p4_w7_coco_384x288_20220705.log.json) |
| [pose_swin_l](/configs/body_2d_keypoint/topdown_heatmap/coco/td-hm_swin-l-p4-w7_8xb32-210e_coco-256x192.py) | 256x192 | 0.743 | 0.906 | 0.821 | 0.798 | 0.943 | [ckpt](https://download.openmmlab.com/mmpose/top_down/swin/swin_l_p4_w7_coco_256x192-642a89db_20220705.pth) | [log](https://download.openmmlab.com/mmpose/top_down/swin/swin_l_p4_w7_coco_256x192_20220705.log.json) |
| [pose_swin_l](/configs/body_2d_keypoint/topdown_heatmap/coco/td-hm_swin-l-p4-w7_8xb32-210e_coco-384x288.py) | 384x288 | 0.763 | 0.912 | 0.830 | 0.814 | 0.949 | [ckpt](https://download.openmmlab.com/mmpose/top_down/swin/swin_l_p4_w7_coco_384x288-c36b7845_20220705.pth) | [log](https://download.openmmlab.com/mmpose/top_down/swin/swin_l_p4_w7_coco_384x288_20220705.log.json) |