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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 26–50 of 66 papers

TitleStatusHype
Consistency-based Self-supervised Learning for Temporal Anomaly LocalizationCode1
Weakly-supervised Video Anomaly Detection with Robust Temporal Feature Magnitude LearningCode1
Weakly Supervised Video Anomaly Detection via Center-guided Discriminative LearningCode1
Anomaly detection in surveillance videos using transformer based attention modelCode1
Aligning First, Then Fusing: A Novel Weakly Supervised Multimodal Violence Detection MethodCode1
Anomaly Detection in Video via Self-Supervised and Multi-Task LearningCode1
Diversity-Measurable Anomaly DetectionCode1
Dual‑detector Re‑optimization for Federated Weakly Supervised Video Anomaly Detection Via Adaptive Dynamic Recursive MappingCode1
FastAno: Fast Anomaly Detection via Spatio-temporal Patch TransformationCode1
ADNet: Temporal Anomaly Detection in Surveillance VideosCode1
A Background-Agnostic Framework with Adversarial Training for Abnormal Event Detection in VideoCode1
Iterative weak/self-supervised classification framework for abnormal events detectionCode1
Multiple Instance-Based Video Anomaly Detection using Deep Temporal Encoding-DecodingCode0
MTFL: Multi-Timescale Feature Learning for Weakly-Supervised Anomaly Detection in Surveillance VideosCode0
Anomaly Detection in Video Sequence with Appearance-Motion CorrespondenceCode0
A MIL Approach for Anomaly Detection in Surveillance Videos from Multiple Camera ViewsCode0
Hybrid Deep Network for Anomaly DetectionCode0
Abnormal event detection on BMTT-PETS 2017 surveillance challengeCode0
Graph Convolutional Label Noise Cleaner: Train a Plug-and-play Action Classifier for Anomaly DetectionCode0
HR-Crime: Human-Related Anomaly Detection in Surveillance Videos—0
3D ResNet with Ranking Loss Function for Abnormal Activity Detection in Videos—0
Abnormal Event Detection In Videos Using Deep Embedding—0
A Hierarchical Spatio-Temporal Graph Convolutional Neural Network for Anomaly Detection in Videos—0
A multi-stream deep neural network with late fuzzy fusion for real-world anomaly detection—0
Anomalous Event Recognition in Videos Based on Joint Learningof Motion and Appearance with Multiple Ranking Measures—0
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