Multi-person human pose estimation is defined as the task of detecting the poses (or keypoints) of all people from an input image.
Existing approaches can be categorized into top-down and bottom-up approaches.
Top-down methods (e.g. deeppose) divide the task into two stages: human detection and pose estimation. They perform human detection first, followed by single-person pose estimation given human bounding boxes.
Bottom-up approaches (e.g. AE) first detect all the keypoints and then group/associate them into person instances.
## Data preparation
Please follow [DATA Preparation](/docs/en/tasks/2d_body_keypoint.md) to prepare data.
## Demo
Please follow [Demo](/demo/docs/2d_human_pose_demo.md#2d-human-pose-demo) to run demos.
title={Ai challenger: A large-scale dataset for going deeper in image understanding},
author={Wu, Jiahong and Zheng, He and Zhao, Bo and Li, Yixin and Yan, Baoming and Liang, Rui and Wang, Wenjia and Zhou, Shipei and Lin, Guosen and Fu, Yanwei and others},
journal={arXiv preprint arXiv:1711.06475},
year={2017}
}
```
</details>
Results on AIC validation set without multi-scale test
| Arch | Input Size | AP | AP<sup>50</sup> | AP<sup>75</sup> | AR | AR<sup>50</sup> | ckpt | log |
title={Ai challenger: A large-scale dataset for going deeper in image understanding},
author={Wu, Jiahong and Zheng, He and Zhao, Bo and Li, Yixin and Yan, Baoming and Liang, Rui and Wang, Wenjia and Zhou, Shipei and Lin, Guosen and Fu, Yanwei and others},
journal={arXiv preprint arXiv:1711.06475},
year={2017}
}
```
</details>
Results on AIC validation set without multi-scale test
| Arch | Input Size | AP | AP<sup>50</sup> | AP<sup>75</sup> | AR | AR<sup>50</sup> | ckpt | log |
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}
}
```
</details>
Results on COCO val2017 without multi-scale test
| Arch | Input Size | AP | AP<sup>50</sup> | AP<sup>75</sup> | AR | AR<sup>50</sup> | ckpt | log |
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}
}
```
</details>
Results on COCO val2017 without multi-scale test
| Arch | Input Size | AP | AP<sup>50</sup> | AP<sup>75</sup> | AR | AR<sup>50</sup> | ckpt | log |
