@inproceedings{hu2018squeeze,
title={Squeeze-and-excitation networks},
author={Hu, Jie and Shen, Li and Sun, Gang},
booktitle={Proceedings of the IEEE conference on computer vision and pattern recognition},
pages={7132--7141},
year={2018}
}
@inproceedings{andriluka14cvpr,
author = {Mykhaylo Andriluka and Leonid Pishchulin and Peter Gehler and Schiele, Bernt},
title = {2D Human Pose Estimation: New Benchmark and State of the Art Analysis},
booktitle = {IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},
year = {2014},
month = {June}
}
Results on MPII val set
Arch | Input Size | Mean | Mean@0.1 | ckpt | log |
---|---|---|---|---|---|
pose_seresnet_50 | 256x256 | 0.884 | 0.292 | ckpt | log |
pose_seresnet_101 | 256x256 | 0.884 | 0.295 | ckpt | log |
pose_seresnet_152* | 256x256 | 0.884 | 0.287 | ckpt | log |
Note that * means without imagenet pre-training.