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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 2130 of 66 papers

TitleStatusHype
Regularity Learning via Explicit Distribution Modeling for Skeletal Video Anomaly DetectionCode1
FastAno: Fast Anomaly Detection via Spatio-temporal Patch TransformationCode1
Real-Time Anomaly Detection and Feature Analysis Based on Time Series for Surveillance VideoCode1
Weakly Supervised Video Anomaly Detection via Center-guided Discriminative LearningCode1
ADNet: Temporal Anomaly Detection in Surveillance VideosCode1
MIST: Multiple Instance Self-Training Framework for Video Anomaly DetectionCode1
Weakly-supervised Video Anomaly Detection with Robust Temporal Feature Magnitude LearningCode1
Iterative weak/self-supervised classification framework for abnormal events detectionCode1
Anomaly Detection in Video via Self-Supervised and Multi-Task LearningCode1
Online Anomaly Detection in Surveillance Videos with Asymptotic Bounds on False Alarm RateCode1
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