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Anomaly Detection In Surveillance Videos

"The goal of a practical anomaly detection system is to timely signal an activity that deviates normal patterns and identify the time window of the occurring anomaly. [It] can be considered as coarse level video understanding, which filters out anomalies from normal patterns." A critical task in video surveillance is detecting anomalous events such as traffic accidents, crimes or illegal activities. Anomalous events rarely occur as compared to normal activities. Hence the application of this task is to "alleviate the waste of labor and time, developing intelligent computer vision algorithms for automatic video anomaly detection".

(Credit: Real-world Anomaly Detection in Surveillance Videos)

Papers

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Showing 41–50 of 66 papers

TitleStatusHype
A Hierarchical Spatio-Temporal Graph Convolutional Neural Network for Anomaly Detection in Videos—0
A multi-stream deep neural network with late fuzzy fusion for real-world anomaly detection—0
Anomalous Event Recognition in Videos Based on Joint Learningof Motion and Appearance with Multiple Ranking Measures—0
Anomaly Detection in Video Sequence With Appearance-Motion Correspondence—0
Any-Shot Sequential Anomaly Detection in Surveillance Videos—0
Are pre-trained CNNs good feature extractors for anomaly detection in surveillance videos?—0
A Scalable and Generalized Deep Learning Framework for Anomaly Detection in Surveillance Videos—0
Continual Learning for Anomaly Detection in Surveillance Videos—0
Contrastive-Regularized U-Net for Video Anomaly Detection—0
CRCL: Causal Representation Consistency Learning for Anomaly Detection in Surveillance Videos—0
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