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.