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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 3140 of 66 papers

TitleStatusHype
Weakly Supervised Video Anomaly Detection via Center-guided Discriminative LearningCode1
VFP290K: A Large-Scale Benchmark Dataset for Vision-based Fallen Person DetectionCode1
A Background-Agnostic Framework with Adversarial Training for Abnormal Event Detection in VideoCode1
Uncertainty-Weighted Image-Event Multimodal Fusion for Video Anomaly DetectionCode1
Iterative weak/self-supervised classification framework for abnormal events detectionCode1
Learning Prompt-Enhanced Context Features for Weakly-Supervised Video Anomaly DetectionCode1
Learning Memory-guided Normality for Anomaly DetectionCode1
HR-Crime: Human-Related Anomaly Detection in Surveillance Videos0
3D ResNet with Ranking Loss Function for Abnormal Activity Detection in Videos0
Abnormal Event Detection In Videos Using Deep Embedding0
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