Technology of Graphic & Image
|
App. Res. of Comp. Printed Article
Vol. 40, 2023 No. 10
3162-3167,3172

Video anomaly detection combining with contrastive memory network

Li Wenzhong
Wu Kewei
Sun Yongxuan
Jiao Chang
Xiong Sixuan
School of Computer Science & Information Engineering, Hefei University of Technology, Hefei 230601, China
DOI: 10.19734/j.issn.1001-3695.2022.12.0829

Abstract

Anomaly detection aims to capture the discriminative features with limited training samples. However, when some anomalies share common compositional patterns with the normal training data, the model likely reconstructs the anomalies well, leading to the miss detection of anomalies. To mitigate this drawback, this paper proposed a novel contrastive memory network, which used the contrast learning framework to separate the sample features based on the autoencoder, and then designed a memory network to suppress the normal features similar to anomaly. This method proposed a two-stage framework for detecting abnormal events. In the first stage, the method used contrastive learning to increase the difference between normal features and abnormal features, and gained representation to be the augment memory and suppression memory of memory network. In the second stage, the model used augment memory to record multi-time normal behavior features, and used suppression memory to constrain the expression of pseudo anomaly items in the augment memory. The AUC value reached 83.26% on UCF Crime datasets and 87.53% on ShanghaiTech datasets, which were 1.14% and 2.43% higher than the existing methods. The results demonstrate that this method can efficiently predict the temporal localization of anomaly events.

Foundation Support

安徽省重点研究与开发计划资助项目(202004d07020004)
安徽省自然科学基金资助项目(2108085MF203)
中央高校基本科研业务费专项资金资助项目(PA2021GDSK0072,JZ2021HGQA0219)

Publish Information

DOI: 10.19734/j.issn.1001-3695.2022.12.0829
Publish at: Application Research of Computers Printed Article, Vol. 40, 2023 No. 10
Section: Technology of Graphic & Image
Pages: 3162-3167,3172
Serial Number: 1001-3695(2023)10-043-3162-06

Publish History

[2023-03-16] Accepted Paper
[2023-10-05] Printed Article

Cite This Article

李文中, 吴克伟, 孙永宣, 等. 基于对比记忆网络的弱监督视频异常检测 [J]. 计算机应用研究, 2023, 40 (10): 3162-3167,3172. (Li Wenzhong, Wu Kewei, Sun Yongxuan, et al. Video anomaly detection combining with contrastive memory network [J]. Application Research of Computers, 2023, 40 (10): 3162-3167,3172. )

About the Journal

  • Application Research of Computers Monthly Journal
  • Journal ID ISSN 1001-3695
    CN  51-1196/TP

Application Research of Computers, founded in 1984, is an academic journal of computing technology sponsored by Sichuan Institute of Computer Sciences under the Science and Technology Department of Sichuan Province.

Aiming at the urgently needed cutting-edge technology in this discipline, Application Research of Computers reflects the mainstream technology, hot technology and the latest development trend of computer application research at home and abroad in a timely manner. The main contents of the journal include high-level academic papers in this discipline, the latest scientific research results and major application results. The contents of the columns involve new theories of computer discipline, basic computer theory, algorithm theory research, algorithm design and analysis, blockchain technology, system software and software engineering technology, pattern recognition and artificial intelligence, architecture, advanced computing, parallel processing, database technology, computer network and communication technology, information security technology, computer image graphics and its latest hot application technology.

Application Research of Computers has many high-level readers and authors, and its readers are mainly senior and middle-level researchers and engineers engaged in the field of computer science, as well as teachers and students majoring in computer science and related majors in colleges and universities. Over the years, the total citation frequency and Web download rate of Application Research of Computers have been ranked among the top of similar academic journals in this discipline, and the academic papers published are highly popular among the readers for their novelty, academics, foresight, orientation and practicality.

Indexed & Evaluation

  • The Second National Periodical Award 100 Key Journals
  • Double Effect Journal of China Journal Formation
  • the Core Journal of China (Peking University 2023 Edition)
  • the Core Journal for Science
  • Chinese Science Citation Database (CSCD) Source Journals
  • RCCSE Chinese Core Academic Journals
  • Journal of China Computer Federation
  • 2020-2022 The World Journal Clout Index (WJCI) Report of Scientific and Technological Periodicals
  • Full-text Source Journal of China Science and Technology Periodicals Database
  • Source Journal of China Academic Journals Comprehensive Evaluation Database
  • Source Journals of China Academic Journals (CD-ROM Version), China Journal Network
  • 2017-2019 China Outstanding Academic Journals with International Influence (Natural Science and Engineering Technology)
  • Source Journal of Top Academic Papers (F5000) Program of China's Excellent Science and Technology Journals
  • Source Journal of China Engineering Technology Electronic Information Network and Electronic Technology Literature Database
  • Source Journal of British Science Digest (INSPEC)
  • Japan Science and Technology Agency (JST) Source Journal
  • Russian Journal of Abstracts (AJ, VINITI) Source Journals
  • Full-text Journal of EBSCO, USA
  • Cambridge Scientific Abstracts (Natural Sciences) (CSA(NS)) core journals
  • Poland Copernicus Index (IC)
  • Ulrichsweb (USA)