# Projects based on MMAction2

There are many research works and projects built on MMAction2.

We list some of them as examples of how to extend MMAction2 for your own projects.

As the page might not be completed, please feel free to create a PR to update this page.

## Projects as an extension

- [OTEAction2](https://github.com/openvinotoolkit/mmaction2): OpenVINO Training Extensions for Action Recognition.

## Projects of papers

There are also projects released with papers.

Some of the papers are published in top-tier conferences (CVPR, ICCV, and ECCV), the others are also highly influential.

To make this list also a reference for the community to develop and compare new video understanding algorithms, we list them following the time order of top-tier conferences.

Methods already supported and maintained by MMAction2 are not listed.

- Evidential Deep Learning for Open Set Action Recognition, ICCV 2021 Oral. [[paper]](https://arxiv.org/abs/2107.10161)[[github]](https://github.com/Cogito2012/DEAR)

- Rethinking Self-supervised Correspondence Learning: A Video Frame-level Similarity Perspective, ICCV 2021 Oral. [[paper]](https://arxiv.org/abs/2103.17263)[[github]](https://github.com/xvjiarui/VFS)

- MGSampler: An Explainable Sampling Strategy for Video Action Recognition, ICCV 2021. [[paper]](https://arxiv.org/abs/2104.09952)[[github]](https://github.com/MCG-NJU/MGSampler)

- MultiSports: A Multi-Person Video Dataset of Spatio-Temporally Localized Sports Actions, ICCV 2021. [[paper]](https://arxiv.org/abs/2105.07404)

- Video Swin Transformer. [[paper]](https://arxiv.org/abs/2106.13230)[[github]](https://github.com/SwinTransformer/Video-Swin-Transformer)

- Long Short-Term Transformer for Online Action Detection. [[paper]](https://arxiv.org/abs/2107.03377)