PRTR: Pose Recognition with Cascade Transformers

Introduction

This repository is the official implementation for Pose Recognition with Cascade Transformers. It proposes two types of cascade Transformers, as follows, for pose recognition.

Two-stage Transformers

Please refer to README.md for detailed usage of the two-stage model variant.

Sequential Transformers

Please refer to annotated_prtr.ipynb for implementation of the sequential (end-to-end) model variant.

For more details, please see Pose Recognition with Cascade Transformers by Ke Li*, Shijie Wang*, Xiang Zhang*, Yifan Xu, Weijian Xu, and Zhuowen Tu.

Updates

04/19/2021: Illustrative code for sequential PRTR is released
04/24/2021: Code, logs, and pre-trained models for two-stage PRTR are released

Citation

@InProceedings{Li_2021_CVPR,
    author    = {Li, Ke and Wang, Shijie and Zhang, Xiang and Xu, Yifan and Xu, Weijian and Tu, Zhuowen},
    title     = {Pose Recognition With Cascade Transformers},
    booktitle = {Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
    month     = {June},
    year      = {2021},
    pages     = {1944-1953}
}

License

This repository is released under the Apache License 2.0. License can be found in LICENSE file.

Acknowledgments

This project is based on the following open source repositories, which greatly facilitate our research.

Thanks to DETR for the implementation of Detection Transformer
Thanks to HRNet-Human-Pose-Estimation for the training and evaluation pipeline
Thanks to HRNet-Image-Classification for HRNet backbone implementation

tian984/PRTR