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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 1–25 of 66 papers

TitleStatusHype
Dual‑detector Re‑optimization for Federated Weakly Supervised Video Anomaly Detection Via Adaptive Dynamic Recursive MappingCode1
Uncertainty-Weighted Image-Event Multimodal Fusion for Video Anomaly DetectionCode1
ProDisc-VAD: An Efficient System for Weakly-Supervised Anomaly Detection in Video Surveillance ApplicationsCode1
CRCL: Causal Representation Consistency Learning for Anomaly Detection in Surveillance Videos—0
STEAD: Spatio-Temporal Efficient Anomaly Detection for Time and Compute Sensitive ApplicationsCode1
Aligning First, Then Fusing: A Novel Weakly Supervised Multimodal Violence Detection MethodCode1
Weakly-Supervised Anomaly Detection in Surveillance Videos Based on Two-Stream I3D Convolution Network—0
MTFL: Multi-Timescale Feature Learning for Weakly-Supervised Anomaly Detection in Surveillance VideosCode0
Abnormal Event Detection In Videos Using Deep Embedding—0
A Scalable and Generalized Deep Learning Framework for Anomaly Detection in Surveillance Videos—0
Distilling Aggregated Knowledge for Weakly-Supervised Video Anomaly Detection—0
Multi-scale Bottleneck Transformer for Weakly Supervised Multimodal Violence DetectionCode1
MULDE: Multiscale Log-Density Estimation via Denoising Score Matching for Video Anomaly DetectionCode2
BatchNorm-based Weakly Supervised Video Anomaly DetectionCode1
VALD-GAN: video anomaly detection using latent discriminator augmented GAN—0
STemGAN: spatio-temporal generative adversarial network for video anomaly detection—0
A MIL Approach for Anomaly Detection in Surveillance Videos from Multiple Camera ViewsCode0
Learning Prompt-Enhanced Context Features for Weakly-Supervised Video Anomaly DetectionCode1
Learning Weakly Supervised Audio-Visual Violence Detection in Hyperbolic SpaceCode1
Contrastive-Regularized U-Net for Video Anomaly Detection—0
Diversity-Measurable Anomaly DetectionCode1
Generating Anomalies for Video Anomaly Detection With Prompt-Based Feature Mapping—0
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
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