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Found 3 papers, 2 papers with code
Learning Asynchronous and Sparse Human-Object Interaction in Videos
Their interactions are sparse in time hence more faithful to the true underlying nature and more robust in inference and learning.
Learning to Abstract and Predict Human Actions
We propose Hierarchical Encoder-Refresher-Anticipator, a multi-level neural machine that can learn the structure of human activities by observing a partial hierarchy of events and roll-out such structure into a future prediction in multiple levels of abstraction.
Learning Regularity in Skeleton Trajectories for Anomaly Detection in Videos
Appearance features have been widely used in video anomaly detection even though they contain complex entangled factors.
Ranked #6 on
Video Anomaly Detection
on HR-ShanghaiTech
