4 papers
Forward Consistency Learning with Gated Context Aggregation for Video Anomaly Detection
Jiahao Lyu, Minghua Zhao, Xuewen Huang +5
As a crucial element of public security, video anomaly detection (VAD) aims to measure deviations from normal patterns for various events in real-time surveillance systems. However…
VADMamba: Exploring State Space Models for Fast Video Anomaly Detection
Jiahao Lyu, Minghua Zhao, Jing Hu +3
Video anomaly detection (VAD) methods are mostly CNN-based or Transformer-based, achieving impressive results, but the focus on detection accuracy often comes at the expense of inf…
Appearance Blur-driven AutoEncoder and Motion-guided Memory Module for Video Anomaly Detection
Jiahao Lyu, Minghua Zhao, Jing Hu +4
Video anomaly detection (VAD) often learns the distribution of normal samples and detects the anomaly through measuring significant deviations, but the undesired generalization may…
Bidirectional skip-frame prediction for video anomaly detection with intra-domain disparity-driven attention
Jiahao Lyu, Minghua Zhao, Jing Hu +5
With the widespread deployment of video surveillance devices and the demand for intelligent system development, video anomaly detection (VAD) has become an important part of constr…