Anomaly Detection In Surveillance Videos
36 papers with code • 5 benchmarks • 6 datasets
Benchmarks
These leaderboards are used to track progress in Anomaly Detection In Surveillance Videos
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ShanghaiTech Campus
UCF-Crime
XD-Violence
UBI-Fights
VFP290K
CamNuvem Dataset
Latest papers with no code
VALD-GAN: video anomaly detection using latent discriminator augmented GAN
The most crucial and difficult challenge for intelligent video surveillance is to identify anomalies in a video that comprises anomalous behavior or occurrences.
STemGAN: spatio-temporal generative adversarial network for video anomaly detection
Automatic detection and interpretation of abnormal events have become crucial tasks in large-scale video surveillance systems.
Contrastive-Regularized U-Net for Video Anomaly Detection
We propose to employ a U-Net like structure to model both types of dependencies in a unified structure where the encoder learns global dependencies hierarchically on top of local ones; then the decoder propagates this global information back to the segment level for classification.
Generating Anomalies for Video Anomaly Detection With Prompt-Based Feature Mapping
There also exists a scene gap between virtual and real scenarios, including scene-specific anomalies (events that are abnormal in one scene but normal in another) and scene-specific attributes, such as the viewpoint of the surveillance camera.
FOR THE SAKE OF PRIVACY: SKELETON-BASED SALIENT BEHAVIOR RECOGNITION
Authorities as well as emergency and rescue services have an increasing interest in smart support systems to ensure public safety which includes in particular behavioral analysis of pedestrians by using video surveillance systems.
A multi-stream deep neural network with late fuzzy fusion for real-world anomaly detection
The proposed end-to-end multi-stream architecture performs abnormal event detection with accuracy as high as 84. 48%, which is better than the performance of existing video anomaly detection methods.
A Hierarchical Spatio-Temporal Graph Convolutional Neural Network for Anomaly Detection in Videos
High-level graph representations encode the trajectories of people and the interactions among multiple identities while low-level graph representations encode the local body postures of each person.
Multi-branch Neural Networks for Video Anomaly Detection in Adverse Lighting and Weather Conditions
Automated anomaly detection in surveillance videos has attracted much interest as it provides a scalable alternative to manual monitoring.
HR-Crime: Human-Related Anomaly Detection in Surveillance Videos
We rely on state-of-the-art techniques to build the feature extraction pipeline for human-related anomaly detection.
Anomalous Event Recognition in Videos Based on Joint Learningof Motion and Appearance with Multiple Ranking Measures
We propose a framework, Deep-network with Multiple Ranking Measures(DMRMs), which addresses context-dependency using a joint learning technique for motion and appearance features.
