Showing cs.CVShow all
2 papers · 1 filter
cs.CV2026
Representation--Behavior Alignment for Explainable Weakly-Supervised Video Anomaly Detection
Chao Huang, Pengfei Wei, Kaige Li +4
Multimodal Large Language Models (MLLMs) provide a natural way to make video anomaly detection more explainable. However, their final decisions do not always fully use the discrimi…
cs.CV2026
VFAD: Variational Semantic Prompting Meets Frequency-Adaptive Representation Learning for Zero-Shot Anomaly Detection
Peng Chen, Kaige Li, Wei Wang +5
Zero-shot anomaly detection (ZSAD) aims to detect and localize anomalies in unseen categories without access to target-specific training data. Although recent CLIP-based methods ha…