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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 51–66 of 66 papers

TitleStatusHype
Gait Recognition using FMCW Radar and Temporal Convolutional Deep Neural Networks—0
Weakly and Partially Supervised Learning Frameworks for Anomaly DetectionCode1
Not only Look, but also Listen: Learning Multimodal Violence Detection under Weak SupervisionCode1
Multiple Instance-Based Video Anomaly Detection using Deep Temporal Encoding-DecodingCode0
Continual Learning for Anomaly Detection in Surveillance Videos—0
Any-Shot Sequential Anomaly Detection in Surveillance Videos—0
Learning Memory-guided Normality for Anomaly DetectionCode1
3D ResNet with Ranking Loss Function for Abnormal Activity Detection in Videos—0
Anomaly Detection in Video Sequence With Appearance-Motion Correspondence—0
Anomaly Detection in Video Sequence with Appearance-Motion CorrespondenceCode0
Hybrid Deep Network for Anomaly DetectionCode0
Graph Convolutional Label Noise Cleaner: Train a Plug-and-play Action Classifier for Anomaly DetectionCode0
MIST: Multiple Instance Spatial Transformer NetworkCode1
Are pre-trained CNNs good feature extractors for anomaly detection in surveillance videos?—0
Real-world Anomaly Detection in Surveillance VideosCode1
Abnormal event detection on BMTT-PETS 2017 surveillance challengeCode0
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