Self-supervised attentive generative adversarial networks for video anomaly detection
Video anomaly detection (VAD) refers to the discrimination of unexpected events in videos.
The deep generative model (DGM)-based method learns the regular patterns on normal …
The deep generative model (DGM)-based method learns the regular patterns on normal …
TransCNN: Hybrid CNN and transformer mechanism for surveillance anomaly detection
Surveillance video anomaly detection (SVAD) is a challenging task due to the variations in
object scale, discrimination and unexpected events, the impact of the background, and the …
object scale, discrimination and unexpected events, the impact of the background, and the …
Amp-net: Appearance-motion prototype network assisted automatic video anomaly detection system
As essential tools for industry safety protection, automatic video anomaly detection systems
(AVADS) are designed to detect anomalous events of concern in surveillance videos …
(AVADS) are designed to detect anomalous events of concern in surveillance videos …
Abnormal event detection using deep contrastive learning for intelligent video surveillance system
The continuous developments of urban and industrial environments have increased the
demand for intelligent video surveillance. Deep learning has achieved remarkable …
demand for intelligent video surveillance. Deep learning has achieved remarkable …
Vision-based traffic accident detection and anticipation: A survey
Traffic accident detection and anticipation is an obstinate road safety problem and
painstaking efforts have been devoted. With the rapid growth of video data, Vision-based …
painstaking efforts have been devoted. With the rapid growth of video data, Vision-based …
A new comprehensive benchmark for semi-supervised video anomaly detection and anticipation
Semi-supervised video anomaly detection (VAD) is a critical task in the intelligent
surveillance system. However, an essential type of anomaly in VAD named scene …
surveillance system. However, an essential type of anomaly in VAD named scene …
Influence-aware attention networks for anomaly detection in surveillance videos
Detecting anomalies in videos is a fundamental issue in public security. The majority of
existing deep learning methods often perform anomaly detection based on the behavior or …
existing deep learning methods often perform anomaly detection based on the behavior or …
Context-related video anomaly detection via generative adversarial network
Video anomaly detection is a challenging task because of the scarcity and ambiguity of
abnormal event samples in videos. Predicting future content based on continuous video …
abnormal event samples in videos. Predicting future content based on continuous video …
Deep learning for video anomaly detection: A review
Video anomaly detection (VAD) aims to discover behaviors or events deviating from the
normality in videos. As a long-standing task in the field of computer vision, VAD has …
normality in videos. As a long-standing task in the field of computer vision, VAD has …
Collaborative normality learning framework for weakly supervised video anomaly detection
Video anomaly detection (VAD) under weak supervision aims to temporally locate abnormal
clips using the easy-to-obtain video-level labels. In this brief, we introduce the underlying …
clips using the easy-to-obtain video-level labels. In this brief, we introduce the underlying …