SOTAVerified

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 1120 of 66 papers

TitleStatusHype
Diversity-Measurable Anomaly DetectionCode1
MGFN: Magnitude-Contrastive Glance-and-Focus Network for Weakly-Supervised Video Anomaly DetectionCode1
Normalizing Flows for Human Pose Anomaly DetectionCode1
Self-supervised Sparse Representation for Video Anomaly DetectionCode1
Consistency-based Self-supervised Learning for Temporal Anomaly LocalizationCode1
Modality-Aware Contrastive Instance Learning with Self-Distillation for Weakly-Supervised Audio-Visual Violence DetectionCode1
Anomaly detection in surveillance videos using transformer based attention modelCode1
Attention-based residual autoencoder for video anomaly detectionCode1
Audio-Guided Attention Network for Weakly Supervised Violence DetectionCode1
VFP290K: A Large-Scale Benchmark Dataset for Vision-based Fallen Person DetectionCode1
Show:102550
← PrevPage 2 of 7Next →

No leaderboard results yet.