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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

Showing 110 of 66 papers

TitleStatusHype
MULDE: Multiscale Log-Density Estimation via Denoising Score Matching for Video Anomaly DetectionCode2
Consistency-based Self-supervised Learning for Temporal Anomaly LocalizationCode1
Anomaly detection in surveillance videos using transformer based attention modelCode1
Attention-based residual autoencoder for video anomaly detectionCode1
BatchNorm-based Weakly Supervised Video Anomaly DetectionCode1
Aligning First, Then Fusing: A Novel Weakly Supervised Multimodal Violence Detection MethodCode1
A Background-Agnostic Framework with Adversarial Training for Abnormal Event Detection in VideoCode1
Anomaly Detection in Video via Self-Supervised and Multi-Task LearningCode1
ADNet: Temporal Anomaly Detection in Surveillance VideosCode1
Audio-Guided Attention Network for Weakly Supervised Violence DetectionCode1
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