Contrastive-Regularized U-Net for Video Anomaly Detection
Author:
Affiliation:
1. Department of Computer Science, Faculty of Information and Communication Technology, Universiti Tunku Abdul Rahman, Kampar, Malaysia
2. Department of Electrical Engineering, Faculty of Engineering, University of Malaya, Kuala Lumpur, Malaysia
Funder
Fundamental Research Grant Scheme (FRGS) through the Ministry of Higher Education (MOHE) of Malaysia
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Subject
General Engineering,General Materials Science,General Computer Science,Electrical and Electronic Engineering
Link
http://xplorestaging.ieee.org/ielx7/6287639/10005208/10098744.pdf?arnumber=10098744
Reference51 articles.
1. Margin Learning Embedded Prediction for Video Anomaly Detection with A Few Anomalies
2. Future Frame Prediction for Anomaly Detection - A New Baseline
3. Graph Convolutional Label Noise Cleaner: Train a Plug-And-Play Action Classifier for Anomaly Detection
4. Not only Look, But Also Listen: Learning Multimodal Violence Detection Under Weak Supervision
5. A Revisit of Sparse Coding Based Anomaly Detection in Stacked RNN Framework
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