/MeshTransformer

Research code for CVPR 2021 paper "End-to-End Human Pose and Mesh Reconstruction with Transformers"

Primary LanguagePythonMIT LicenseMIT

MeshTransformer ✨

This is our research code of End-to-End Human Pose and Mesh Reconstruction with Transformers.

MEsh TRansfOrmer is a simple yet effective transformer-based method for human pose and mesh reconsruction from an input image. In this repository, we provide our research code for training and testing our proposed method for the following tasks:

  • Human pose and mesh reconstruction
  • Hand pose and mesh reconstruction

Installation

Check INSTALL.md for installation instructions.

Model Zoo and Download

Please download our pre-trained models and other relevant files that are important to run our code.

Check DOWNLOAD.md for details.

Quick demo

We provide demo codes to run end-to-end inference on the test images.

Check DEMO.md for details.

Experiments

We provide python codes for training and evaluation.

Check EXP.md for details.

Contributing

We welcome contributions and suggestions. Please check CONTRIBUTE and CODE_OF_CONDUCT for details.

Citations

If you find our work useful in your research, please consider citing:

@inproceedings{lin2021end-to-end,
author = {Lin, Kevin and Wang, Lijuan and Liu, Zicheng},
title = {End-to-End Human Pose and Mesh Reconstruction with Transformers},
booktitle = {CVPR},
year = {2021},
}

License

Our research code is released under the MIT license. See LICENSE for details.

We use submodules from third parties, such as huggingface/transformers and hassony2/manopth. Please see NOTICE for details.

We note that any use of SMPL models and MANO models are subject to Software Copyright License for non-commercial scientific research purposes. See SMPL-Model License and MANO License for details.

Acknowledgments

Our implementation and experiments are built on top of open-source GitHub repositories. We thank all the authors who made their code public, which tremendously accelerates our project progress. If you find these works helpful, please consider citing them as well.

huggingface/transformers

HRNet/HRNet-Image-Classification

nkolot/GraphCMR

akanazawa/hmr

MandyMo/pytorch_HMR

hassony2/manopth

hongsukchoi/Pose2Mesh_RELEASE

mks0601/I2L-MeshNet_RELEASE

open-mmlab/mmdetection