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Ruqin Wang

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Open access Jul 2026

Learning Fine-Grained Video Anomaly Detection from Normal Videos

This paper proposes a framework for unsupervised anomaly video generation from solely normal videos, leveraging VLMs to generate structured textual descriptions of anomalies conditioned on the perception of this video.

Ruqin Wang, Yasumasa Tamura, Masahito Yamamoto · 0 citations

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