MetaVD: A Meta Video Dataset for enhancing human action recognition datasets

Yuya Yoshikawa, Yutaro Shigeto, Akikazu Takeuchi

Abstract: Highlights•We construct a meta video dataset for human action recognition, called MetaVD.•MetaVD integrates UCF101, HMDB51, ActivityNet, STAIR Actions, Charades and Kinetics-700.•MetaVD provides four types of relations between action labels across datasets.•We present simple methods to enhance datasets using MetaVD.•Models trained on datasets enhanced by MetaVD achieve high recognition performances.