<!-- [BACKBONE] -->

<details>
<summary align="right"><a href="http://openaccess.thecvf.com/content_cvpr_2018/html/Hu_Squeeze-and-Excitation_Networks_CVPR_2018_paper">SEResNet (CVPR'2018)</a></summary>

```bibtex
@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}
}
```

</details>

<!-- [DATASET] -->

<details>
<summary align="right"><a href="http://openaccess.thecvf.com/content_cvpr_2014/html/Andriluka_2D_Human_Pose_2014_CVPR_paper.html">MPII (CVPR'2014)</a></summary>

```bibtex
@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}
}
```

</details>

Results on MPII val set

| Arch                                                        | Input Size | Mean  | Mean@0.1 |                            ckpt                             |                             log                             |
| :---------------------------------------------------------- | :--------: | :---: | :------: | :---------------------------------------------------------: | :---------------------------------------------------------: |
| [pose_seresnet_50](/configs/body_2d_keypoint/topdown_heatmap/mpii/td-hm_seresnet50_8xb64-210e_mpii-256x256.py) |  256x256   | 0.884 |  0.292   | [ckpt](https://download.openmmlab.com/mmpose/top_down/seresnet/seresnet50_mpii_256x256-1bb21f79_20200927.pth) | [log](https://download.openmmlab.com/mmpose/top_down/seresnet/seresnet50_mpii_256x256_20200927.log.json) |
| [pose_seresnet_101](/configs/body_2d_keypoint/topdown_heatmap/mpii/td-hm_seresnet101_8xb64-210e_mpii-256x256.py) |  256x256   | 0.884 |  0.295   | [ckpt](https://download.openmmlab.com/mmpose/top_down/seresnet/seresnet101_mpii_256x256-0ba14ff5_20200927.pth) | [log](https://download.openmmlab.com/mmpose/top_down/seresnet/seresnet101_mpii_256x256_20200927.log.json) |
| [pose_seresnet_152\*](/configs/body_2d_keypoint/topdown_heatmap/mpii/td-hm_seresnet152_8xb32-210e_mpii-256x256.py) |  256x256   | 0.884 |  0.287   | [ckpt](https://download.openmmlab.com/mmpose/top_down/seresnet/seresnet152_mpii_256x256-6ea1e774_20200927.pth) | [log](https://download.openmmlab.com/mmpose/top_down/seresnet/seresnet152_mpii_256x256_20200927.log.json) |

Note that * means without imagenet pre-training.
