DAMS, a dual-branch architecture fusing adaptive temporal pyramids, CBAM attention, and CLIP pseudo-labels, reports 94.67 AUC on UCF-Crime and 84.00 AP on XD-Violence for weakly supervised video anomaly detection.
Weakly- supervised video anomaly detection with snippet anomalous atten- tion
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DAMS:Dual-Branch Adaptive Multiscale Spatiotemporal Framework for Video Anomaly Detection
DAMS, a dual-branch architecture fusing adaptive temporal pyramids, CBAM attention, and CLIP pseudo-labels, reports 94.67 AUC on UCF-Crime and 84.00 AP on XD-Violence for weakly supervised video anomaly detection.