Video Anomaly Detection (VAD) serves as a pivotal technology in the intelligent surveillance
systems, enabling the temporal or spatial identification of anomalous events within videos …

The increasing utilization of surveillance cameras in smart cities, coupled with the surge of
online video applications, has heightened concerns regarding public security and privacy …

Abstract Video Anomaly Detection (VAD) aims to automatically identify unexpected spatial–
temporal patterns to detect abnormal events in surveillance videos. Existing unsupervised …

Video anomaly detection is an essential yet challenging task in the multimedia community,
with promising applications in smart cities and secure communities. Existing methods …

Video anomaly detection is a critical component of intelligent video surveillance systems,
extensively deployed and researched in industry and academia. However, existing methods …

Video Anomaly Detection (VAD) is an essential yet challenging task in the signal processing
community, which aims to understand the spatial and temporal contextual interactions …

Existing unsupervised video anomaly detection methods often suffer from performance
degradation due to the overgeneralization of deep models. In this paper, we propose a …

The development of modern manufacturing has raised greater demands on the accuracy,
response speed, and operating cost of industrial accident warnings. Compared to …

Abstract Video Anomaly Detection (VAD) is a key technology that enables automatic
anomaly detection in surveillance video systems. Due to the considerable dimensions and …

Video anomaly detection (VAD) has been intensively studied for years because of its
potential applications in intelligent video systems. Existing unsupervised VAD methods tend …