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Anomaly Detection In Surveillance Videos

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"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)

논문

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Anomaly Detection In Surveillance Videos

논문

ADNet: Temporal Anomaly Detection in Surveillance Videos

MIST: Multiple Instance Self-Training Framework for Video Anomaly Detection

Weakly-supervised Video Anomaly Detection with Robust Temporal Feature Magnitude Learning

Anomaly Detection in Video via Self-Supervised and Multi-Task Learning

Online Anomaly Detection in Surveillance Videos with Asymptotic Bounds on False Alarm Rate

A Background-Agnostic Framework with Adversarial Training for Abnormal Event Detection in Video

Localizing Anomalies from Weakly-Labeled Videos

Gait Recognition using FMCW Radar and Temporal Convolutional Deep Neural Networks

Weakly and Partially Supervised Learning Frameworks for Anomaly Detection

Not only Look, but also Listen: Learning Multimodal Violence Detection under Weak Supervision

Multiple Instance-Based Video Anomaly Detection using Deep Temporal Encoding-Decoding

Continual Learning for Anomaly Detection in Surveillance Videos

Any-Shot Sequential Anomaly Detection in Surveillance Videos

Learning Memory-guided Normality for Anomaly Detection

3D ResNet with Ranking Loss Function for Abnormal Activity Detection in Videos

Hybrid Deep Network for Anomaly Detection

Anomaly Detection in Video Sequence with Appearance-Motion Correspondence

Graph Convolutional Label Noise Cleaner: Train a Plug-and-play Action Classifier for Anomaly Detection

MIST: Multiple Instance Spatial Transformer Network

Are pre-trained CNNs good feature extractors for anomaly detection in surveillance videos?

Real-world Anomaly Detection in Surveillance Videos