Bidirectional Spatio-Temporal Feature Learning With Multiscale Evaluation for Video Anomaly Detection-Reference-Cited by-同舟云学术

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Bidirectional Spatio-Temporal Feature Learning With Multiscale Evaluation for Video Anomaly Detection

Published:2022-12 Issue:12 Volume:32 Page:8285-8296
ISSN:1051-8215
Container-title:IEEE Transactions on Circuits and Systems for Video Technology
language:
Short-container-title:IEEE Trans. Circuits Syst. Video Technol.

Author:

Zhong Yuanhong¹^ORCID,Chen Xia¹,Hu Yongting¹,Tang Panliang²,Ren Fan³^ORCID

Affiliation:

1. School of Microelectronics and Communication Engineering, Chongqing University, Chongqing, China

2. China Electronics Technology Group Corporation No. 26 Research Institute, Chongqing, China

3. Changan Software Technology Company, Changan Automobile Corporation, Chongqing, China

Funder

Special Project of Technological Innovation and Application Development of Chongqing

National Natural Science Foundation of China

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Electrical and Electronic Engineering,Media Technology

Link

http://xplorestaging.ieee.org/ielx7/76/9973795/09828496.pdf?arnumber=9828496

Reference52 articles.

1. Attention is all you need;vaswani;Proc 31st Annu Conf Neural Inf Process Systems,2017

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

3. Object Detection Networks on Convolutional Feature Maps

4. Object Classification Using CNN-Based Fusion of Vision and LIDAR in Autonomous Vehicle Environment

5. Semi-Supervised Adapted HMMs for Unusual Event Detection

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