ActivityNet

A large-scale video benchmark for human activity understanding. Provides samples from 203 activity classes with an average of 137 untrimmed videos per class and 1.41 activity instances per video, for a total of 849 video hours. The benchmark covers a wide range of complex human activities that are of interest to people in their daily living and can be used to compare algorithms for three scenarios: untrimmed video classification, trimmed activity classification, and activity detection.

Released

Unknown

Readiness

Paper only

Primary field

General AI

Benchmark Radar records only publicly supported details and links back to primary sources for verification.