mmpose/configs/body_2d_keypoint/topdown_heatmap/crowdpose/resnet_crowdpose.md

SimpleBaseline2D (ECCV'2018)

@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}
}

ResNet (CVPR'2016)

@inproceedings{he2016deep,
  title={Deep residual learning for image recognition},
  author={He, Kaiming and Zhang, Xiangyu and Ren, Shaoqing and Sun, Jian},
  booktitle={Proceedings of the IEEE conference on computer vision and pattern recognition},
  pages={770--778},
  year={2016}
}

CrowdPose (CVPR'2019)

@article{li2018crowdpose,
  title={CrowdPose: Efficient Crowded Scenes Pose Estimation and A New Benchmark},
  author={Li, Jiefeng and Wang, Can and Zhu, Hao and Mao, Yihuan and Fang, Hao-Shu and Lu, Cewu},
  journal={arXiv preprint arXiv:1812.00324},
  year={2018}
}

Results on CrowdPose test with YOLOv3 human detector

Arch	Input Size	AP	AP50	AP75	AP (E)	AP (M)	AP (H)	ckpt	log
pose_resnet_50	256x192	0.637	0.808	0.692	0.738	0.650	0.506	ckpt	log
pose_resnet_101	256x192	0.647	0.810	0.703	0.745	0.658	0.521	ckpt	log
pose_resnet_101	320x256	0.661	0.821	0.714	0.759	0.672	0.534	ckpt	log
pose_resnet_152	256x192	0.656	0.818	0.712	0.754	0.666	0.533	ckpt	log