Action Recognition by Hierarchical Mid-level Action Elements

ICCV 2015 Tian LanYuke ZhuAmir Roshan ZamirSilvio Savarese

Realistic videos of human actions exhibit rich spatiotemporal structures at multiple levels of granularity: an action can always be decomposed into multiple finer-grained elements in both space and time. To capture this intuition, we propose to represent videos by a hierarchy of mid-level action elements (MAEs), where each MAE corresponds to an action-related spatiotemporal segment in the video... (read more)

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