ShufflenetV2 (ECCV'2018)
```bibtex
@inproceedings{ma2018shufflenet,
title={Shufflenet v2: Practical guidelines for efficient cnn architecture design},
author={Ma, Ningning and Zhang, Xiangyu and Zheng, Hai-Tao and Sun, Jian},
booktitle={Proceedings of the European conference on computer vision (ECCV)},
pages={116--131},
year={2018}
}
```
COCO (ECCV'2014)
```bibtex
@inproceedings{lin2014microsoft,
title={Microsoft coco: Common objects in context},
author={Lin, Tsung-Yi and Maire, Michael and Belongie, Serge and Hays, James and Perona, Pietro and Ramanan, Deva and Doll{\'a}r, Piotr and Zitnick, C Lawrence},
booktitle={European conference on computer vision},
pages={740--755},
year={2014},
organization={Springer}
}
```
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_shufflenetv2](/configs/body_2d_keypoint/topdown_heatmap/coco/td-hm_shufflenetv2_8xb64-210e_coco-256x192.py) | 256x192 | 0.602 | 0.857 | 0.672 | 0.668 | 0.902 | [ckpt](https://download.openmmlab.com/mmpose/v1/body_2d_keypoint/topdown_heatmap/coco/td-hm_shufflenetv2_8xb64-210e_coco-256x192-51fb931e_20221014.pth) | [log](https://download.openmmlab.com/mmpose/v1/body_2d_keypoint/topdown_heatmap/coco/td-hm_shufflenetv2_8xb64-210e_coco-256x192_20221014.log) |
| [pose_shufflenetv2](/configs/body_2d_keypoint/topdown_heatmap/coco/td-hm_shufflenetv2_8xb64-210e_coco-384x288.py) | 384x288 | 0.638 | 0.866 | 0.707 | 0.699 | 0.910 | [ckpt](https://download.openmmlab.com/mmpose/v1/body_2d_keypoint/topdown_heatmap/coco/td-hm_shufflenetv2_8xb64-210e_coco-384x288-d30ab55c_20221014.pth) | [log](https://download.openmmlab.com/mmpose/v1/body_2d_keypoint/topdown_heatmap/coco/td-hm_shufflenetv2_8xb64-210e_coco-384x288_20221014.log) |