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Found 4 papers, 2 papers with code
Video Abnormal Event Detection by Learning to Complete Visual Cloze Tests
With each patch and the patch sequence of a STC compared to a visual "word" and "sentence" respectively, we deliberately erase a certain "word" (patch) to yield a VCT.
Deep Anomaly Discovery From Unlabeled Videos via Normality Advantage and Self-Paced Refinement
With this property, we propose Localization based Reconstruction (LBR) as a strong UVAD baseline and a solid foundation of our solution.
Multi-view Deep One-class Classification: A Systematic Exploration
Third, to remedy the problem that limited benchmark datasets are available for multi-view deep OCC, we extensively collect existing public data and process them into more than 30 new multi-view benchmark datasets via multiple means, so as to provide a publicly available evaluation platform for multi-view deep OCC.
Cloze Test Helps: Effective Video Anomaly Detection via Learning to Complete Video Events
To build such a visual cloze test, a certain patch of STC is erased to yield an incomplete event (IE).
Ranked #14 on
Anomaly Detection
on CUHK Avenue
