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 …

This article summarizes research trends on the topic of anomaly detection in video feeds of a
single scene. We discuss the various problem formulations, publicly available datasets and …

Anomaly detection is commonly pursued as a one-class classification problem, where
models can only learn from normal training samples, while being evaluated on both normal …

Anomaly detection in video is a challenging computer vision problem. Due to the lack of
anomalous events at training time, anomaly detection requires the design of learning …

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 …

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 …

Increasing scene-awareness is a key challenge in video anomaly detection (VAD). In this
work, we propose a hierarchical semantic contrast (HSC) method to learn a scene-aware …

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 is commonly used in many applications, such as security
surveillance, and is very challenging. A majority of recent video anomaly detection …

Abnormal event detection in video is a complex computer vision problem that has attracted
significant attention in recent years. The complexity of the task arises from the commonly …