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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 31–40 of 66 papers

TitleStatusHype
A multi-stream deep neural network with late fuzzy fusion for real-world anomaly detection—0
Audio-Guided Attention Network for Weakly Supervised Violence DetectionCode1
VFP290K: A Large-Scale Benchmark Dataset for Vision-based Fallen Person DetectionCode1
A Hierarchical Spatio-Temporal Graph Convolutional Neural Network for Anomaly Detection in Videos—0
Regularity Learning via Explicit Distribution Modeling for Skeletal Video Anomaly DetectionCode1
10 Security and Privacy Problems in Large Foundation Models—0
Multi-branch Neural Networks for Video Anomaly Detection in Adverse Lighting and Weather Conditions—0
HR-Crime: Human-Related Anomaly Detection in Surveillance Videos—0
FastAno: Fast Anomaly Detection via Spatio-temporal Patch TransformationCode1
Real-Time Anomaly Detection and Feature Analysis Based on Time Series for Surveillance VideoCode1
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