hrnet_coco.md

DEKR (CVPR'2021)

@inproceedings{geng2021bottom,
  title={Bottom-up human pose estimation via disentangled keypoint regression},
  author={Geng, Zigang and Sun, Ke and Xiao, Bin and Zhang, Zhaoxiang and Wang, Jingdong},
  booktitle={Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition},
  pages={14676--14686},
  year={2021}
}

HRNet (CVPR'2019)

@inproceedings{sun2019deep,
  title={Deep high-resolution representation learning for human pose estimation},
  author={Sun, Ke and Xiao, Bin and Liu, Dong and Wang, Jingdong},
  booktitle={Proceedings of the IEEE conference on computer vision and pattern recognition},
  pages={5693--5703},
  year={2019}
}

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 without multi-scale test

Arch	Input Size	AP	AP50	AP75	AR	AR50	ckpt	log
HRNet-w32	512x512	0.680	0.868	0.745	0.728	0.897	ckpt	log
HRNet-w48	640x640	0.709	0.876	0.773	0.758	0.909	ckpt	log

Results on COCO val2017 with multi-scale test. 3 default scales ([2, 1, 0.5]) are used

Arch	Input Size	AP	AP50	AP75	AR	AR50	ckpt
HRNet-w32*	512x512	0.705	0.878	0.767	0.759	0.921	ckpt
HRNet-w48*	640x640	0.722	0.882	0.785	0.778	0.928	ckpt

* these configs are generally used for evaluation. The training settings are identical to their single-scale counterparts.

The results of models provided by the authors on COCO val2017 using the same evaluation protocol

Arch	Input Size	Setting	AP	AP50	AP75	AR	AR50	ckpt
HRNet-w32	512x512	single-scale	0.678	0.868	0.744	0.728	0.897	see official implementation
HRNet-w48	640x640	single-scale	0.707	0.876	0.773	0.757	0.909	see official implementation
HRNet-w32	512x512	multi-scale	0.708	0.880	0.773	0.763	0.921	see official implementation
HRNet-w48	640x640	multi-scale	0.721	0.881	0.786	0.779	0.927	see official implementation

The discrepancy between these results and that shown in paper is attributed to the differences in implementation details in evaluation process.