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 …

Weakly supervised video anomaly detection (WSVAD) is a challenging task. Generating fine-
grained pseudo-labels based on weak-label and then self-training a classifier is currently a …

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 …

Current video anomaly detection (VAD) approaches with weak supervisions are inherently
limited to a closed-set setting and may struggle in open-world applications where there can …

Abstract ecent progress in video anomaly detection suggests that the features of
appearance and motion play crucial roles in distinguishing abnormal patterns from normal …

Video anomaly detection (VAD) has been paid increasing attention due to its potential
applications, its current dominant tasks focus on online detecting anomalies, which can be …

Interpreting camera data is key for autonomously acting systems such as autonomous
vehicles. Vision systems that operate in real-world environments must be able to understand …

Current weakly supervised video anomaly detection (WSVAD) task aims to achieve frame-
level anomalous event detection with only coarse video-level annotations available. Existing …

Video anomaly detection (VAD) plays a crucial role in intelligent surveillance. However, an
essential type of anomaly named scene-dependent anomaly is overlooked. Moreover, the …

Video anomaly detection research is generally evaluated on short isolated benchmark
videos only a few minutes long. However in real-world environments security cameras …