Detecting abnormal events in video is commonly framed as a one-class classification task,
where training videos contain only normal events, while test videos encompass both normal …

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 …

Weakly supervised video anomaly detection (WS-VAD) is to distinguish anomalies from
normal events based on discriminative representations. Most existing works are limited in …

Anomaly detection in surveillance videos is a challenging computer vision task where only
normal videos are available during training. Recent work released the first virtual anomaly …

Video anomaly detection is a challenging task owing to the rare and diverse nature of
abnormal events. However, most of the existing methods only learn the normality in a single …

Anomaly detection in the video is an important research area and a challenging task in real
applications. Due to the unavailability of large-scale annotated anomaly events, most …

Video anomaly detection is of critical practical importance to a variety of real applications
because it allows human attention to be focused on events that are likely to be of interest, in …

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

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 …

Abnormal event detection in video is a challenging vision problem. Most existing
approaches formulate abnormal event detection as an outlier detection task, due to the …