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cs.CV2026
MMVIAD: Multi-view Multi-task Video Understanding for Industrial Anomaly Detection
Xiran Zhao, Jing Jin, Yan Bai +6
Industrial anomaly detection is critical for manufacturing quality control, yet existing datasets mainly focus on static images or sparse views, which do not fully reflect continuo…
cs.CV2026
Multi-turn Physics-informed Vision-language Model for Physics-grounded Anomaly Detection
Yao Gu, Xiaohao Xu, Yingna Wu
Vision-Language Models (VLMs) demonstrate strong general-purpose reasoning but remain limited in physics-grounded anomaly detection, where causal understanding of dynamics is essen…