Author

Fan Lyu

2 papers indexed here

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2026

Reconstructive Visual Tuning for Weakly Supervised Video Anomaly Detection

Weakly supervised video anomaly detection (WS-VAD) presents a significant challenge in security video surveillance, as it aims to accurately identify anomaly frames in untrimmed videos with only video-level supervision. Several recent studies exploit vision-language pre-training models, e.g., CLIP, to take advantage of...

Shuang-Qing Zhang, Wei Xu, Yu-Qi Fang et al. · IEEE Transactions on Informa... · 2 citations

#small language model Preprint Sep 2026

Probe-VAD: Ordinal Likelihood Probing for Training-Free Video Anomaly Detection

Probe-VAD is proposed, an ordinal binary-probing framework that directly probes severity preferences from a frozen VLM, providing a simple interface for translating frozen VLM visual understanding into continuous, rank-sensitive anomaly scores without task-specific training or caption-based compression.

Jia-Wei Gu, Qi-Lin Zhao, Teng-Kuo Guo et al. · 1 citation