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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
Distilling Aggregated Knowledge for Weakly-Supervised Video Anomaly Detection—0
FOR THE SAKE OF PRIVACY: SKELETON-BASED SALIENT BEHAVIOR RECOGNITION—0
Gait Recognition using FMCW Radar and Temporal Convolutional Deep Neural Networks—0
Generating Anomalies for Video Anomaly Detection With Prompt-Based Feature Mapping—0
10 Security and Privacy Problems in Large Foundation Models—0
Multi-branch Neural Networks for Video Anomaly Detection in Adverse Lighting and Weather Conditions—0
STemGAN: spatio-temporal generative adversarial network for video anomaly detection—0
VALD-GAN: video anomaly detection using latent discriminator augmented GAN—0
Weakly-Supervised Anomaly Detection in Surveillance Videos Based on Two-Stream I3D Convolution Network—0
Hybrid Deep Network for Anomaly DetectionCode0
A MIL Approach for Anomaly Detection in Surveillance Videos from Multiple Camera ViewsCode0
Graph Convolutional Label Noise Cleaner: Train a Plug-and-play Action Classifier for Anomaly DetectionCode0
Anomaly Detection in Video Sequence with Appearance-Motion CorrespondenceCode0
Multiple Instance-Based Video Anomaly Detection using Deep Temporal Encoding-DecodingCode0
MTFL: Multi-Timescale Feature Learning for Weakly-Supervised Anomaly Detection in Surveillance VideosCode0
Abnormal event detection on BMTT-PETS 2017 surveillance challengeCode0
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