Video Anomaly Detection via Visual Cloze Tests
Author:
Affiliation:
1. College of Computer Science and Technology, National University of Defense Technology, Changsha, China
2. School of Cyberspace Science, Dongguan University of Technology, Dongguan, China
Funder
National Natural Science Foundation of China
Science and Technology Innovation Program of Hunan Province
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Subject
Computer Networks and Communications,Safety, Risk, Reliability and Quality
Link
http://xplorestaging.ieee.org/ielx7/10206/9970396/10197574.pdf?arnumber=10197574
Reference94 articles.
1. Object-Centric Auto-Encoders and Dummy Anomalies for Abnormal Event Detection in Video
2. Appearance-Motion Memory Consistency Network for Video Anomaly Detection
3. Joint Detection and Recounting of Abnormal Events by Learning Deep Generic Knowledge
4. Learning Normal Dynamics in Videos with Meta Prototype Network
5. Autoencoding beyond pixels using a learned similarity metric;larsen;Proc Int Conf Mach Learn,2016
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