December 4, 2025InformationOpen Access

Enhancing Weakly Supervised Video Anomaly Detection with Object-Centric Features

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Incorporating object-centric features led to advanced anomaly detection capabilities.
The approach highlighted the importance of including semantics, addressing challenges of weak supervision.
Experimental validation on UCF-Crime and ShanghaiTech datasets demonstrated competitive performance with state-of-the-art methods.
The findings underscore the potential impact of semantic-aware strategies on improving video surveillance systems.

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Analysis improves anomaly detection in videos by integrating object detection with spatio-temporal dynamics, suggesting a semantic-aware approach.

Yang Chen (2025) studied this question.

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Analysis improves anomaly detection in videos by integrating object detection with spatio-temporal dynamics, suggesting a semantic-aware approach.