A Large-Scale Video Benchmark for Human Activity Understanding

Our benchmark aims at covering a wide range of complex human activities that are of interest to people in their daily living. We illustrate three scenarios in which ActivityNet can be used to compare algorithms for human activity understanding: global video classification,trimmed activity classification and activity detection.

200
CLASSES
100
UNTRIMMED VIDEOS PER CLASS
1.54
ACTIVITY INSTANCES PER VIDEO
648
VIDEO HOURS