Explainable Anomaly Detection for Context Semantic Awareness
Résumé
We introduce an explainable neural network for Unsupervised Video Anomaly Detection (UVAD). Video Anomaly Detection (VAD) is a critical area of research with extensive applications, especially in surveillance and security systems deployed in public spaces such as roads, factories, and shopping malls. The significance of VAD lies in its capacity to enhance safety and security measures by identifying unusual events or activities without requiring manually labeled abnormal videos for training.
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