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https://github.com/open-mmlab/mmskeleton
A OpenMMLAB toolbox for human pose estimation, skeleton-based action recognition, and action synthesis.
https://github.com/open-mmlab/mmskeleton
action-recognition deep-learning graph-convolutional-network pytorch skeleton-based-action-recognition
Last synced: about 1 month ago
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A OpenMMLAB toolbox for human pose estimation, skeleton-based action recognition, and action synthesis.
- Host: GitHub
- URL: https://github.com/open-mmlab/mmskeleton
- Owner: open-mmlab
- License: apache-2.0
- Created: 2017-11-21T09:01:44.000Z (over 6 years ago)
- Default Branch: master
- Last Pushed: 2022-11-25T20:02:00.000Z (over 1 year ago)
- Last Synced: 2024-04-22T20:24:37.302Z (2 months ago)
- Topics: action-recognition, deep-learning, graph-convolutional-network, pytorch, skeleton-based-action-recognition
- Language: Python
- Homepage:
- Size: 91.2 MB
- Stars: 2,849
- Watchers: 71
- Forks: 1,020
- Open Issues: 201
-
Metadata Files:
- Readme: README.md
- License: LICENSE
Lists
- awesome-stars - mmskeleton - A OpenMMLAB toolbox for human pose estimation, skeleton-based action recognition, and action synthesis. (Python)
- awesome-list - MMSkeleton - A OpenMMLAB toolbox for human pose estimation, skeleton-based action recognition, and action synthesis (Computer Vision / General Purpose CV)
- StarryDivineSky - open-mmlab/mmskeleton
README
# MMSkeleton
## Introduction
MMSkeleton is an open source toolbox for skeleton-based human understanding.
It is a part of the [open-mmlab](https://github.com/open-mmlab) project in the charge of [Multimedia Laboratory, CUHK](http://mmlab.ie.cuhk.edu.hk/).
MMSkeleton is developed on our research project [ST-GCN](https://github.com/yysijie/st-gcn/blob/master/OLD_README.md).
## Updates
- [2020-01-21] MMSkeleton v0.7 is released.
- [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
- **High extensibility**
MMSkeleton provides a flexible framework for organizing codes and projects systematically, with the ability to extend to various tasks and scale up to complex deep models.
- **Multiple tasks**
MMSkeleton addresses to multiple tasks in human understanding, including but not limited to:
- [x] [skeleton-based action recognition (ST-GCN)](./doc/START_RECOGNITION.md)
- [x] [2D pose estimation](./doc/START_POSE_ESTIMATION.md)
- [ ] skeleton-based action generation
- [ ] 3D pose estimation
- [ ] pose tracking
- [x] [build custom skeleton-based dataset](./doc/CUSTOM_DATASET.md)
- [x] [create your own applications](./doc/CREATE_APPLICATION.md)
## Getting Started
Please see [GETTING_STARTED.md](./doc/GETTING_STARTED.md) for more details of MMSkeleton.
## License
The project is release under the [Apache 2.0 license](./LICENSE).
## Contributing
We appreciate all contributions to improve MMSkeleton.
Please refer to [CONTRIBUTING.md](./doc/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]
```