AVA: A Video Dataset of Spatio-temporally Localized Atomic Visual Actions

CVPR 2018 Chunhui Gu • Chen Sun • David A. Ross • Carl Vondrick • Caroline Pantofaru • Yeqing Li • Sudheendra Vijayanarasimhan • George Toderici • Susanna Ricco • Rahul Sukthankar • Cordelia Schmid • Jitendra Malik

The AVA dataset densely annotates 80 atomic visual actions in 430 15-minute video clips, where actions are localized in space and time, resulting in 1.58M action labels with multiple labels per person occurring frequently. The key characteristics of our dataset are: (1) the definition of atomic visual actions, rather than composite actions; (2) precise spatio-temporal annotations with possibly multiple annotations for each person; (3) exhaustive annotation of these atomic actions over 15-minute video clips; (4) people temporally linked across consecutive segments; and (5) using movies to gather a varied set of action representations. We will release the dataset publicly.

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