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 …

Video Surveillance (VS) systems are popular. For enhancing the safety of public lives as
well as assets, it is utilized in public places like marketplaces, hospitals, streets, education …

In this paper, we propose HF2-VAD, a Hybrid framework that integrates Flow reconstruction
and Frame prediction seamlessly to handle Video Anomaly Detection. Firstly, we design the …

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 …

A self-supervised multi-task learning (SSMTL) framework for video anomaly detection was
recently introduced in literature. Due to its highly accurate results, the method attracted the …

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 …

Whether it is used for predictive maintenance, intrusion detection or surveillance, on-device
anomaly detection is a very valuable functionality in sensor and Internet-of-things (IoT) …

Automated anomaly detection in surveillance videos has attracted much interest as it
provides a scalable alternative to manual monitoring. Most existing approaches achieve …

Abnormal event detection is one of the most challenging tasks in computer vision. Many
existing deep anomaly detection models are based on reconstruction errors, where the …

We propose a very fast frame-level model for anomaly detection in video, which learns to
detect anomalies by distilling knowledge from multiple highly accurate object-level teacher …