DeeperAction aims to advance the area of video understanding with a shift from traditional action recognition to deeper understanding tasks of action, with a focus on detailed understanding of human action and anomaly recognition from videos in the wild. Specifically, we benchmark five related tasks on detailed action understanding by introducing newly-annotated and high-quality datasets, and organize the video action understanding challenge on these benchmarks.