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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 Background-Agnostic Framework with Adversarial Training for Abnormal Event Detection in VideoCode1
Localizing Anomalies from Weakly-Labeled VideosCode1
Weakly and Partially Supervised Learning Frameworks for Anomaly DetectionCode1
Not only Look, but also Listen: Learning Multimodal Violence Detection under Weak SupervisionCode1
Learning Memory-guided Normality for Anomaly DetectionCode1
MIST: Multiple Instance Spatial Transformer NetworkCode1
Real-world Anomaly Detection in Surveillance VideosCode1
CRCL: Causal Representation Consistency Learning for Anomaly Detection in Surveillance Videos—0
Weakly-Supervised Anomaly Detection in Surveillance Videos Based on Two-Stream I3D Convolution Network—0
MTFL: Multi-Timescale Feature Learning for Weakly-Supervised Anomaly Detection in Surveillance VideosCode0
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