State-of-the-art pose-based video anomaly detection models achieve over 52% frame-level AUC-ROC but drop below 10% event-level precision and 0.11 average F1 when evaluated with temporal action localization metrics on standard benchmarks.
Hierarchical graph em- bedded pose regularity learning via spatio-temporal trans- former for abnormal behavior detection
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From Frames to Events: Rethinking Evaluation in Human-Centric Video Anomaly Detection
State-of-the-art pose-based video anomaly detection models achieve over 52% frame-level AUC-ROC but drop below 10% event-level precision and 0.11 average F1 when evaluated with temporal action localization metrics on standard benchmarks.