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 …

Surveillance cameras have recently been utilized to provide physical security services
globally in diverse private and public spaces. The number of cameras has been increasing …

Anomaly detection with weakly supervised video-level labels is typically formulated as a
multiple instance learning (MIL) problem, in which we aim to identify snippets containing …

Video anomaly detection is well investigated in weakly supervised and one-class
classification (OCC) settings. However, unsupervised video anomaly detection is quite …

Learning to detect real-world anomalous events through video-level labels is a challenging
task due to the rare occurrence of anomalies as well as noise in the labels. In this work, we …

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 …

Anomalous behavior identification is the process of detecting behavior that differs from its
normal. These incidents will vary from violence to war, road crashes to kidnap**, and so …

Fall event detection has been a research hotspot in recent years in the fields of medicine
and health. Currently, vision-based fall detection methods have been considered the most …

This paper proposes a novel weakly supervised approach for anomaly detection, which
begins with a relation-aware feature extractor to capture the multi-scale convolutional neural …

Due to the limited availability of anomaly examples, video anomaly detection is often seen
as one-class classification (OCC) problem. A popular way to tackle this problem is by …