Frame-Level Efficient Video Anomaly Detection Based on Prototype Networks-Reference-Cited by-同舟云学术

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Frame-Level Efficient Video Anomaly Detection Based on Prototype Networks

Published:2024-06-24 Issue: Volume: Page:534-539
ISSN:
Container-title:2024 IEEE International Conference on Real-time Computing and Robotics (RCAR)
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Author:

Wang Kexin¹,Lu Baoli²,Zhou Yuxi¹,Wang Congcong¹,He Yu³,Zhang Jianhua¹

Affiliation:

1. Tianjin University of Technology,School of Computer Science and Engineering,Tianjin,China

2. Chinese Academy of Sciences,AnnLab, Institute of Semiconductors,Beijing,China,100083

3. Chinese Academy of Sciences,Technology and Engineering Center for Space Utilization,Beijing,China

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx8/10670697/10670719/10670895.pdf?arnumber=10670895

Reference25 articles.

1. Anomaly Detection and Localization in Crowded Scenes

2. Abnormal Event Detection at 150 FPS in MATLAB

3. A Revisit of Sparse Coding Based Anomaly Detection in Stacked RNN Framework

4. Spatial–temporal pooling for action recognition in videos

5. Online detection of unusual events in videos via dynamic sparse coding

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