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 …

Visual anomaly detection addresses the problem of classification or localization of regions in
an image that deviate from their normal appearance. A popular approach trains an auto …

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 …

Anomaly detection in surveillance videos is currently a challenge because of the diversity of
possible events. We propose a deep convolutional neural network (CNN) that addresses …

Anomaly detection in videos refers to the identification of events that do not conform to
expected behavior. However, almost all existing methods tackle the problem by minimizing …

A popular method for anomaly detection is to use the generator of an adversarial network to
formulate anomaly score over reconstruction loss of input. Due to the rare occurrence of …

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 …

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 …