RTMPose (arXiv'2023)
```bibtex
@misc{https://doi.org/10.48550/arxiv.2303.07399,
doi = {10.48550/ARXIV.2303.07399},
url = {https://arxiv.org/abs/2303.07399},
author = {Jiang, Tao and Lu, Peng and Zhang, Li and Ma, Ningsheng and Han, Rui and Lyu, Chengqi and Li, Yining and Chen, Kai},
keywords = {Computer Vision and Pattern Recognition (cs.CV), FOS: Computer and information sciences, FOS: Computer and information sciences},
title = {RTMPose: Real-Time Multi-Person Pose Estimation based on MMPose},
publisher = {arXiv},
year = {2023},
copyright = {Creative Commons Attribution 4.0 International}
}
```
RTMDet (arXiv'2022)
```bibtex
@misc{lyu2022rtmdet,
title={RTMDet: An Empirical Study of Designing Real-Time Object Detectors},
author={Chengqi Lyu and Wenwei Zhang and Haian Huang and Yue Zhou and Yudong Wang and Yanyi Liu and Shilong Zhang and Kai Chen},
year={2022},
eprint={2212.07784},
archivePrefix={arXiv},
primaryClass={cs.CV}
}
```
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.
- `Face6` and `*` denote model trained on 6 public datasets:
- [COCO-Wholebody-Face](https://github.com/jin-s13/COCO-WholeBody/)
- [WFLW](https://wywu.github.io/projects/LAB/WFLW.html)
- [300W](https://ibug.doc.ic.ac.uk/resources/300-W/)
- [COFW](http://www.vision.caltech.edu/xpburgos/ICCV13/)
- [Halpe](https://github.com/Fang-Haoshu/Halpe-FullBody/)
- [LaPa](https://github.com/JDAI-CV/lapa-dataset)
| Config | Input Size | NME
(LaPa) | FLOPS
(G) | Download |
| :--------------------------------------------------------------------------: | :--------: | :----------------: | :---------------: | :-----------------------------------------------------------------------------: |
| [RTMPose-t\*](./rtmpose/face_2d_keypoint/rtmpose-t_8xb256-120e_face6-256x256.py) | 256x256 | 1.67 | 0.652 | [Model](https://download.openmmlab.com/mmpose/v1/projects/rtmposev1/rtmpose-t_simcc-face6_pt-in1k_120e-256x256-df79d9a5_20230529.pth) |
| [RTMPose-s\*](./rtmpose/face_2d_keypoint/rtmpose-s_8xb256-120e_face6-256x256.py) | 256x256 | 1.59 | 1.119 | [Model](https://download.openmmlab.com/mmpose/v1/projects/rtmposev1/rtmpose-s_simcc-face6_pt-in1k_120e-256x256-d779fdef_20230529.pth) |
| [RTMPose-m\*](./rtmpose/face_2d_keypoint/rtmpose-m_8xb256-120e_face6-256x256.py) | 256x256 | 1.44 | 2.852 | [Model](https://download.openmmlab.com/mmpose/v1/projects/rtmposev1/rtmpose-m_simcc-face6_pt-in1k_120e-256x256-72a37400_20230529.pth) |