Skip to content

Spatial Temporal Graph Convolutional Networks (ST-GCN) for Skeleton-Based Action Recognition in PyTorch

License

Notifications You must be signed in to change notification settings

ioir123ju/mmskeleton

 
 

Repository files navigation

MMSkeleton

Introduction

MMSkeleton is an open source toolbox for skeleton-based human understanding. It is a part of the open-mmlab project in the charge of Multimedia Laboratory, CUHK. MMSkeleton is developed on our research project ST-GCN.

Updates

  • [2019-10-09] MMSkeleton v0.6 is released.
  • [2019-10-08] Support model zoo.
  • [2019-10-02] Support custom dataset.
  • [2019-09-23] Add video-based pose estimation demo.
  • [2019-08-29] MMSkeleton v0.5 is released.

Features

Getting Started

Please see GETTING_STARTED.md for more details of MMSkeleton.

License

The project is release under the Apache 2.0 license.

Contributing

We appreciate all contributions to improve MMSkeleton. Please refer to CONTRIBUTING.md for the contributing guideline.

Citation

Please cite the following paper if you use this repository in your reseach.

@misc{mmskeleton2019,
  author =       {Sijie Yan, Yuanjun Xiong, Jingbo Wang, Dahua Lin},
  title =        {MMSkeleton},
  howpublished = {\url{https://github.com/open-mmlab/mmskeleton}},
  year =         {2019}
}

Contact

For any question, feel free to contact

Sijie Yan     : [email protected]
Jingbo Wang   : [email protected]
Yuanjun Xiong : [email protected]

About

Spatial Temporal Graph Convolutional Networks (ST-GCN) for Skeleton-Based Action Recognition in PyTorch

Resources

License

Stars

Watchers

Forks

Packages

No packages published

Languages

  • Cuda 61.2%
  • Python 38.7%
  • Other 0.1%