mmpose/configs/body_2d_keypoint/topdown_heatmap/coco/resnest_coco.md

ResNeSt (ArXiv'2020)

@article{zhang2020resnest,
  title={ResNeSt: Split-Attention Networks},
  author={Zhang, Hang and Wu, Chongruo and Zhang, Zhongyue and Zhu, Yi and Zhang, Zhi and Lin, Haibin and Sun, Yue and He, Tong and Muller, Jonas and Manmatha, R. and Li, Mu and Smola, Alexander},
  journal={arXiv preprint arXiv:2004.08955},
  year={2020}
}

COCO (ECCV'2014)

@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_resnest_50	256x192	0.720	0.899	0.800	0.775	0.939	ckpt	log
pose_resnest_50	384x288	0.737	0.900	0.811	0.789	0.937	ckpt	log
pose_resnest_101	256x192	0.725	0.900	0.807	0.781	0.939	ckpt	log
pose_resnest_101	384x288	0.745	0.905	0.818	0.798	0.942	ckpt	log
pose_resnest_200	256x192	0.731	0.905	0.812	0.787	0.943	ckpt	log
pose_resnest_200	384x288	0.753	0.907	0.827	0.805	0.943	ckpt	log
pose_resnest_269	256x192	0.737	0.907	0.819	0.792	0.943	ckpt	log
pose_resnest_269	384x288	0.754	0.908	0.828	0.805	0.943	ckpt	log