Videos represent the primary source of information for surveillance applications. Video
material is often available in large quantities but in most cases it contains little or no …

Surveillance cameras have recently been utilized to provide physical security services
globally in diverse private and public spaces. The number of cameras has been increasing …

Appearance features have been widely used in video anomaly detection even though they
contain complex entangled factors. We propose a new method to model the normal patterns …

Detecting anomalies in surveillance videos has long been an important but unsolved
problem. In particular, many existing solutions are overly sensitive to (often ephemeral) …

Abnormal event detection in large videos is an important task in research and industrial
applications, which has attracted considerable attention in recent years. Existing methods …

Crowd anomaly detection is a key research area in vision-based surveillance. Most of the
crowd anomaly detection algorithms are either too slow, bulky, or power-hungry to be …

There is an increasing demand for automated video surveillance with a wide range of
threats in the society and less manpower to monitor them. Especially, detecting violence in …

Recently, most state-of-the-art anomaly detection methods are based on apparent motion
and appearance reconstruction networks and use error estimation between generated and …

In this paper, we present an approach to detect and localize anomalies in the surveillance
videos. Precise detection, modeling the normality in a context and dealing with false alarms …

Existing state-of-the-a rt (SOTA) video anomaly detection methods have mainly focused on
the network design for obtaining their performance improvements. Different to the main …