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Mobilenetv2: Inverted residuals and linear bottlenecks

Introduction

[BACKBONE]

@inproceedings{sandler2018mobilenetv2,
  title={Mobilenetv2: Inverted residuals and linear bottlenecks},
  author={Sandler, Mark and Howard, Andrew and Zhu, Menglong and Zhmoginov, Andrey and Chen, Liang-Chieh},
  booktitle={Proceedings of the IEEE conference on computer vision and pattern recognition},
  pages={4510--4520},
  year={2018}
}

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_mobilenetv2 256x192 0.646 0.874 0.723 0.707 0.917 ckpt log
pose_mobilenetv2 384x288 0.673 0.879 0.743 0.729 0.916 ckpt log

Results on MPII val set

Arch Input Size Mean Mean@0.1 ckpt log
pose_mobilenetv2 256x256 0.854 0.235 ckpt log