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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 1–50 of 66 papers

TitleStatusHype
MULDE: Multiscale Log-Density Estimation via Denoising Score Matching for Video Anomaly DetectionCode2
Learning Weakly Supervised Audio-Visual Violence Detection in Hyperbolic SpaceCode1
Localizing Anomalies from Weakly-Labeled VideosCode1
MGFN: Magnitude-Contrastive Glance-and-Focus Network for Weakly-Supervised Video Anomaly DetectionCode1
MIST: Multiple Instance Self-Training Framework for Video Anomaly DetectionCode1
MIST: Multiple Instance Spatial Transformer NetworkCode1
Modality-Aware Contrastive Instance Learning with Self-Distillation for Weakly-Supervised Audio-Visual Violence DetectionCode1
STEAD: Spatio-Temporal Efficient Anomaly Detection for Time and Compute Sensitive ApplicationsCode1
Attention-based residual autoencoder for video anomaly detectionCode1
Self-supervised Sparse Representation for Video Anomaly DetectionCode1
Multi-scale Bottleneck Transformer for Weakly Supervised Multimodal Violence DetectionCode1
Normalizing Flows for Human Pose Anomaly DetectionCode1
Not only Look, but also Listen: Learning Multimodal Violence Detection under Weak SupervisionCode1
Online Anomaly Detection in Surveillance Videos with Asymptotic Bounds on False Alarm RateCode1
ProDisc-VAD: An Efficient System for Weakly-Supervised Anomaly Detection in Video Surveillance ApplicationsCode1
Real-Time Anomaly Detection and Feature Analysis Based on Time Series for Surveillance VideoCode1
Real-world Anomaly Detection in Surveillance VideosCode1
Regularity Learning via Explicit Distribution Modeling for Skeletal Video Anomaly DetectionCode1
Audio-Guided Attention Network for Weakly Supervised Violence DetectionCode1
BatchNorm-based Weakly Supervised Video Anomaly DetectionCode1
Consistency-based Self-supervised Learning for Temporal Anomaly LocalizationCode1
Anomaly detection in surveillance videos using transformer based attention modelCode1
Weakly and Partially Supervised Learning Frameworks for Anomaly DetectionCode1
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
Weakly-supervised Video Anomaly Detection with Robust Temporal Feature Magnitude LearningCode1
ADNet: Temporal Anomaly Detection in Surveillance VideosCode1
Weakly Supervised Video Anomaly Detection via Center-guided Discriminative LearningCode1
VFP290K: A Large-Scale Benchmark Dataset for Vision-based Fallen Person DetectionCode1
A Background-Agnostic Framework with Adversarial Training for Abnormal Event Detection in VideoCode1
Uncertainty-Weighted Image-Event Multimodal Fusion for Video Anomaly DetectionCode1
Iterative weak/self-supervised classification framework for abnormal events detectionCode1
Learning Prompt-Enhanced Context Features for Weakly-Supervised Video Anomaly DetectionCode1
Learning Memory-guided Normality for Anomaly DetectionCode1
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
Anomaly Detection in Video Sequence With Appearance-Motion Correspondence—0
Any-Shot Sequential Anomaly Detection in Surveillance Videos—0
Are pre-trained CNNs good feature extractors for anomaly detection in surveillance videos?—0
A Scalable and Generalized Deep Learning Framework for Anomaly Detection in Surveillance Videos—0
Continual Learning for Anomaly Detection in Surveillance Videos—0
Contrastive-Regularized U-Net for Video Anomaly Detection—0
CRCL: Causal Representation Consistency Learning for Anomaly Detection in Surveillance Videos—0
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