YOLO-Pose (CVPRW'2022)
```bibtex
@inproceedings{maji2022yolo,
title={Yolo-pose: Enhancing yolo for multi person pose estimation using object keypoint similarity loss},
author={Maji, Debapriya and Nagori, Soyeb and Mathew, Manu and Poddar, Deepak},
booktitle={Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition},
pages={2637--2646},
year={2022}
}
```
YOLOX
```bibtex
@article{ge2021yolox,
title={Yolox: Exceeding yolo series in 2021},
author={Ge, Zheng and Liu, Songtao and Wang, Feng and Li, Zeming and Sun, Jian},
journal={arXiv preprint arXiv:2107.08430},
year={2021}
}
```
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
| Arch | Input Size | AP | AP50 | AP75 | AR | AR50 | ckpt | log |
| :-------------------------------------------- | :--------: | :---: | :-------------: | :-------------: | :---: | :-------------: | :-------------------------------------------: | :-------------------------------------------: |
| [yoloxpose_tiny](/configs/body_2d_keypoint/yoloxpose/coco/yoloxpose_tiny_4xb64-300e_coco-416.py) | 416x416 | 0.526 | 0.793 | 0.556 | 0.571 | 0.833 | [ckpt](https://download.openmmlab.com/mmpose/v1/body_2d_keypoint/yolox_pose/yoloxpose_tiny_4xb64-300e_coco-416-76eb44ca_20230829.pth) | [log](https://download.openmmlab.com/mmpose/v1/body_2d_keypoint/yolox_pose/yoloxpose_tiny_4xb64-300e_coco-416-20230829.json) |
| [yoloxpose_s](/configs/body_2d_keypoint/yoloxpose/coco/yoloxpose_s_8xb32-300e_coco-640.py) | 640x640 | 0.641 | 0.872 | 0.702 | 0.682 | 0.902 | [ckpt](https://download.openmmlab.com/mmpose/v1/body_2d_keypoint/yolox_pose/yoloxpose_s_8xb32-300e_coco-640-56c79c1f_20230829.pth) | [log](https://download.openmmlab.com/mmpose/v1/body_2d_keypoint/yolox_pose/yoloxpose_s_8xb32-300e_coco-640-20230829.json) |
| [yoloxpose_m](/configs/body_2d_keypoint/yoloxpose/coco/yoloxpose_m_8xb32-300e_coco-640.py) | 640x640 | 0.695 | 0.899 | 0.766 | 0.733 | 0.926 | [ckpt](https://download.openmmlab.com/mmpose/v1/body_2d_keypoint/yolox_pose/yoloxpose_m_8xb32-300e_coco-640-84e9a538_20230829.pth) | [log](https://download.openmmlab.com/mmpose/v1/body_2d_keypoint/yolox_pose/yoloxpose_m_8xb32-300e_coco-640-20230829.json) |
| [yoloxpose_l](/configs/body_2d_keypoint/yoloxpose/coco/yoloxpose_l_8xb32-300e_coco-640.py) | 640x640 | 0.712 | 0.901 | 0.782 | 0.749 | 0.926 | [ckpt](https://download.openmmlab.com/mmpose/v1/body_2d_keypoint/yolox_pose/yoloxpose_l_8xb32-300e_coco-640-de0f8dee_20230829.pth) | [log](https://download.openmmlab.com/mmpose/v1/body_2d_keypoint/yolox_pose/yoloxpose_l_8xb32-300e_coco-640-20230829.json) |