Video Surveillance (VS) systems are popular. For enhancing the safety of public lives as
well as assets, it is utilized in public places like marketplaces, hospitals, streets, education …

An outlier is a datum that is far from other data points in which it occurs. It can have a
considerable impact on the output. Therefore, removing or resolving it before the analysis is …

With the widespread use of closed-circuit television (CCTV) surveillance systems in public
areas, crowd anomaly detection has become an increasingly critical aspect of the intelligent …

Learning multiple pretext tasks is a popular approach to tackle the nonalignment problem in
unsupervised video anomaly detection. However, the conventional learning method of …

Video anomaly detection aims to automatically identify unusual objects or behaviours by
learning from normal videos. Previous methods tend to use simplistic reconstruction or …

Anomalous event recognition requires an instant response to reduce the loss of human life
and property; however, existing automated systems show limited performance due to …

Video anomaly detection aims to detect the segments containing abnormal events from
video sequence, which is a current research hotspot due to the importance in maintaining …

In contemporary society, surveillance anomaly detection, ie, spotting anomalous events
such as crimes or accidents in surveillance videos, is a critical task. As anomalies occur …

Video Anomaly detection, aiming to detect the abnormal behaviors in surveillance videos, is
a challenging task since the anomalous events are diversified and complicated in different …

Anomaly detection in video surveillance aims to detect anomalous frames whose properties
significantly differ from normal patterns. Anomalies in videos can occur in both spatial …