CVPR2020

FineGym: A Hierarchical Video Dataset for Fine-Grained Action Understanding

Dian Shao, Yue Zhao, Bo Dai, Dahua Lin

摘要

Balance Beam Floor Exercise Balance Beam Beam-turns Leap-Jump-Hop BB-flight-handspring 3 turn in tuck stand Wolf jump--hip angle at 45, knees together Flic-flac with step-out Tree Reasoning Tree Reasoning Tree Reasoning Sets Elements More Fine-grained Events level of granularity presents significant challenges for action recognition, e.g. how to parse the temporal structures from a coherent action, and how to distinguish between subtly different action classes. We systematically investigate representative methods on this dataset and obtain a number of interesting findings. We hope this dataset could advance research towards action understanding.