Multi-scale spatiotemporal normality learning for unsupervised video anomaly detection

Caitian Liu; Li Gong; Xiong Chen

doi:10.1007/s10489-025-06485-3

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Multi-scale spatiotemporal normality learning for unsupervised video anomaly detection

Caitian Liu Li Gong Xiong Chen

Year: 2025 Journal: Applied Intelligence Vol: 55 (7) Publisher: Springer Science+Business Media

DOI: 10.1007/s10489-025-06485-3

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Keywords:

Computer science Normality Anomaly detection Scale (ratio) Artificial intelligence Pattern recognition (psychology) Anomaly (physics) Unsupervised learning Machine learning Statistics Cartography Mathematics

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Anomaly Detection Techniques and Applications

Physical Sciences → Computer Science → Artificial Intelligence

Network Security and Intrusion Detection

Physical Sciences → Computer Science → Computer Networks and Communications

Artificial Immune Systems Applications

Physical Sciences → Engineering → Biomedical Engineering

Multi-scale spatiotemporal normality learning for unsupervised video anomaly detection

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