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ResNetV1D

Introduction

[BACKBONE]

@inproceedings{he2019bag,
  title={Bag of tricks for image classification with convolutional neural networks},
  author={He, Tong and Zhang, Zhi and Zhang, Hang and Zhang, Zhongyue and Xie, Junyuan and Li, Mu},
  booktitle={Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition},
  pages={558--567},
  year={2019}
}

Results and models

2d Human Pose Estimation

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_resnetv1d_50 256x192 0.722 0.897 0.799 0.777 0.933 ckpt log
pose_resnetv1d_50 384x288 0.730 0.900 0.799 0.780 0.934 ckpt log
pose_resnetv1d_101 256x192 0.731 0.899 0.809 0.786 0.938 ckpt log
pose_resnetv1d_101 384x288 0.748 0.902 0.816 0.799 0.939 ckpt log
pose_resnetv1d_152 256x192 0.737 0.902 0.812 0.791 0.940 ckpt log
pose_resnetv1d_152 384x288 0.752 0.909 0.821 0.802 0.944 ckpt log

Results on MPII val set

Arch Input Size Mean [email protected] ckpt log
pose_resnetv1d_50 256x256 0.881 0.290 ckpt log
pose_resnetv1d_101 256x256 0.883 0.295 ckpt log
pose_resnetv1d_152 256x256 0.888 0.300 ckpt log