In this paper we address the abnormality detection problem in crowded scenes. We propose to use Generative Adversarial Nets (GANs), which are trained using normal frames and …
We present an efficient method for detecting anomalies in videos. Recent applications of convolutional neural networks have shown promises of convolutional layers for object …
Modeling pedestrian dynamics and their implementation in a computer are challenging and important issues in the knowledge areas of transportation and computer simulation. The aim …
Anomalous event detection is of utmost importance in intelligent video surveillance. Currently, most approaches for the automatic analysis of complex video scenes typically rely …
We propose a novel framework for abnormal event detection in video that requires no training sequences. Our framework is based on unmasking, a technique previously used for …
B Yogameena, C Nagananthini - International journal of disaster risk …, 2017 - Elsevier
Computer Vision (CV) based surveillance in crowded scenes is one of the most significant and promising topics due to the increase of people gatherings in public places where the …
R Hinami, T Mei, S Satoh - Proceedings of the IEEE …, 2017 - openaccess.thecvf.com
This paper addresses the problem of joint detection and recounting of abnormal events in videos. Recounting of abnormal events, ie, explaining why they are judged to be abnormal …
This paper proposes a fast and reliable method for anomaly detection and localization in video data showing crowded scenes. Time-efficient anomaly localization is an ongoing …
Y Feng, Y Yuan, X Lu - Neurocomputing, 2017 - Elsevier
Abnormal event detection in video surveillance is extremely important, especially for crowded scenes. In recent years, many algorithms have been proposed based on hand …