Surveillance footage can catch a wide range of realistic anomalies. This research suggests
using a weakly supervised strategy to avoid annotating anomalous segments in training …

Video anomaly detection is a challenging problem due to the ambiguity and diversity of
anomalies in different scenes. In this paper, we present a novel framework to detect …

Camera surveillance is widely used in residential areas, highways, schools and other public
places. The monitoring and scanning of sudden abnormal events depend on humans …

This paper presents an anomaly detection method that is based on a sparse coding inspired
Deep Neural Networks (DNN). Specifically, in light of the success of sparse coding based …

We tackle the complex problem of detecting and recognising anomalies in surveillance
videos at the frame level, utilising only video-level supervision. We introduce the novel …

We address the problem of anomaly detection, that is, detecting anomalous events in a
video sequence. Anomaly detection methods based on convolutional neural networks …

Video Anomaly Detection (VAD) has been traditionally tackled in two main methodologies:
the reconstruction-based approach and the prediction-based one. As the reconstruction …

As essential tools for industry safety protection, automatic video anomaly detection systems
(AVADS) are designed to detect anomalous events of concern in surveillance videos …

Video anomaly detection is well investigated in weakly supervised and one-class
classification (OCC) settings. However, unsupervised video anomaly detection is quite …

Anomaly detection in videos remains a challenging task due to the ambiguous definition of
anomaly and the complexity of visual scenes from real video data. Different from the …