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Associative Embedding (AE) + HRNet

Introduction

@inproceedings{newell2017associative,
  title={Associative embedding: End-to-end learning for joint detection and grouping},
  author={Newell, Alejandro and Huang, Zhiao and Deng, Jia},
  booktitle={Advances in neural information processing systems},
  pages={2277--2287},
  year={2017}
}
@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}
}

Results and models

2d Human Pose Estimation

Results on COCO val2017 without multi-scale test

Arch Input Size AP AP50 AP75 AR AR50 ckpt log
HRNet-w32 512x512 0.654 0.863 0.720 0.710 0.892 ckpt log
HRNet-w48 512x512 0.665 0.860 0.727 0.716 0.889 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 log
HRNet-w32 512x512 0.698 0.877 0.760 0.748 0.907 ckpt log
HRNet-w48 512x512 0.712 0.880 0.771 0.757 0.909 ckpt log

Results on MHP v2.0 validation set without multi-scale test

Arch Input Size AP AP50 AP75 AR AR50 ckpt log
HRNet-w48 512x512 0.583 0.895 0.666 0.656 0.931 ckpt log

Results on MHP v2.0 validation set with multi-scale test. 3 default scales ([2, 1, 0.5]) are used

Arch Input Size AP AP50 AP75 AR AR50 ckpt log
HRNet-w48 512x512 0.592 0.898 0.673 0.664 0.932 ckpt log

Results on AIC validation set without multi-scale test

Arch Input Size AP AP50 AP75 AR AR50 ckpt log
HRNet-w32 512x512 0.303 0.697 0.225 0.373 0.755 ckpt log

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

Arch Input Size AP AP50 AP75 AR AR50 ckpt log
HRNet-w32 512x512 0.318 0.717 0.246 0.379 0.764 ckpt log