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+# 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)