In recent years, designing and testing video anomaly detection methods have focused on
synthetic or unrealistic sequences. This has mainly four drawbacks: 1) events are controlled …

Progress in video anomaly detection research is currently slowed by small datasets that lack
a wide variety of activities as well as flawed evaluation criteria. This paper aims to help move …

Abstract Open Set Video Anomaly Detection (OpenVAD) aims to identify abnormal events
from video data where both known anomalies and novel ones exist in testing. Unsupervised …

Over the past decade, video anomaly detection has been explored with remarkable results.
However, research on methodologies suitable for online performance is still very limited. In …

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 …

Video Surveillance Systems (VSS) are widely utilized in public and private areas to increase
public safety, such as shopping malls, markets, banks, hospitals, educational institutions …

In this paper we address the problem of online video abnormal event detection. A vast
number of methods to automatically detect abnormal events in videos have been recently …

Most video anomaly detection approaches are based on data-intensive end-to-end trained
neural networks, which extract spatiotemporal features from videos. The extracted feature …

Anomaly detection has attracted considerable search attention. However, existing anomaly
detection databases encounter two major problems. Firstly, they are limited in scale …

Detecting anomalous events in videos is one of the most popular computer vision topics. It is
considered a challenging task in video analysis due to its definition, which is subjective or …