Anomaly Detection In Surveillance Videos
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Benchmarks
Most implemented
Real-world Anomaly Detection in Surveillance Videos
Weakly-supervised Video Anomaly Detection with Robust Temporal Feature Magnitude Learning
ADNet: Temporal Anomaly Detection in Surveillance Videos
A Background-Agnostic Framework with Adversarial Training for Abnormal Event Detection in Video
Learning Memory-guided Normality for Anomaly Detection
Papers
Human-Centric Anomaly Detection in Surveillance Videos Using YOLO-World and Spatio-Temporal Deep Learning
Anomaly detection in surveillance videos remains a challenging task due to the diversity of abnormal events, class imbalance, and scene-dependent visual clutter. To address these issues, we propose a robust deep learning…
Anomaly Detection In Surveillance VideosAnomaly ClassificationUnmasking Performance Gaps: A Comparative Study of Human Anonymization and Its Effects on Video Anomaly Detection
Advancements in deep learning have improved anomaly detection in surveillance videos, yet they raise urgent privacy concerns due to the collection of sensitive human data. In this paper, we present a comprehensive analys…
Anomaly Detection In Surveillance VideosVideo Anomaly DetectionDual‑detector Re‑optimization for Federated Weakly Supervised Video Anomaly Detection Via Adaptive Dynamic Recursive Mapping
Federated weakly supervised video anomaly detection represents a significant advancement in privacy-preserving collaborative learning, enabling distributed clients to train anomaly detectors using only video-level annota…
Anomaly DetectionAnomaly Detection In Surveillance VideosEdge-computingFederated Learning+5Uncertainty-Weighted Image-Event Multimodal Fusion for Video Anomaly Detection
Most existing video anomaly detectors rely solely on RGB frames, which lack the temporal resolution needed to capture abrupt or transient motion cues, key indicators of anomalous events. To address this limitation, we pr…
Anomaly DetectionAnomaly Detection In Surveillance VideosVideo Anomaly DetectionVideo UnderstandingProDisc-VAD: An Efficient System for Weakly-Supervised Anomaly Detection in Video Surveillance Applications
Weakly-supervised video anomaly detection (WS-VAD) using Multiple Instance Learning (MIL) suffers from label ambiguity, hindering discriminative feature learning. We propose ProDisc-VAD, an efficient framework tackling t…
Anomaly Detection In Surveillance VideosContrastive LearningMultiple Instance LearningSupervised Anomaly Detection+3CRCL: Causal Representation Consistency Learning for Anomaly Detection in Surveillance Videos
Video Anomaly Detection (VAD) remains a fundamental yet formidable task in the video understanding community, with promising applications in areas such as information forensics and public safety protection. Due to the ra…
Anomaly DetectionAnomaly Detection In Surveillance VideosRepresentation LearningVideo Anomaly Detection+1