MetaVD Dataset | Papers With Code

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MetaVD is a *Meta Video Dataset* for enhancing human action recognition datasets.
It provides human-annotated relationship labels between action classes across human action recognition datasets.
MetaVD is proposed in the following paper:
**Yuya Yoshikawa, Yutaro Shigeto, and Akikazu Takeuchi. "MetaVD: A Meta Video Dataset for enhancing human action recognition datasets." Computer Vision and Image Understanding 212 (2021): 103276. [[link](https://www.sciencedirect.com/science/article/pii/S107731422100120X)]**

MetaVD integrates the following datasets: [UCF101](https://www.crcv.ucf.edu/data/UCF101.php), [HMDB51](https://serre-lab.clps.brown.edu/resource/hmdb-a-large-human-motion-database/), [ActivityNet](http://activity-net.org/), [STAIR Actions](https://actions.stair.center/), [Charades](https://prior.allenai.org/projects/charades), [Kinetics-700](https://deepmind.com/research/open-source/kinetics)

This repository does _NOT_ provide videos in the datasets. 
For information on how to download the videos, please refer to the website of each dataset.

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