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RTMPose (arXiv'2023) 
@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) 
@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-WholeBody (ECCV'2020) 
@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
rtmw-m 256x192 0.676 0.747 0.671 0.794 0.783 0.854 0.491 0.604 0.582 0.673 ckpt -
rtmw-l 256x192 0.743 0.807 0.763 0.868 0.834 0.889 0.598 0.701 0.660 0.746 ckpt -
rtmw-x 256x192 0.746 0.808 0.770 0.869 0.844 0.896 0.610 0.710 0.672 0.752 ckpt -
rtmw-l 384x288 0.761 0.824 0.793 0.885 0.884 0.921 0.663 0.752 0.701 0.780 ckpt -
rtmw-x 384x288 0.763 0.826 0.796 0.888 0.884 0.923 0.664 0.755 0.702 0.781 ckpt -