App. Res. of Comp. Accepted Paper
Vol. 44, 2027 No. 1

Survey on weakly-supervised violent behavior detection

Zhu Yuexiu1
Qing Depeng2
Zheng Yifeng1
1. School of Computer Science, Minnan Normal University, Zhangzhou 363000, China
2. School of Geophysics, China University of Petroleum (Beijing), Beijing 102200, China
DOI: 10.19734/j.issn.1001-3695.2026.05.0135

Abstract

Violent abnormal events exhibit suddenness, sparsity, and scenario complexity. With automatic learning capabilities, deep learning models effectively extract key representative features from specific tasks and scenarios and serve as widely used tools for violent behavior detection. Meanwhile, violent events usually appear in only a few segments of long videos, and fine-grained frame-level or segment-level annotation involves high costs. Therefore, weakly supervised detection has gradually become an important research direction in this field. This paper systematically reviewed recent studies on deep-learning-based weakly supervised violent behavior detection and summarized the research progress of unimodal and multimodal detection methods under weakly supervised learning. First, it analyzed unimodal detection methods from the perspectives of attention mechanisms and multiple-instance learning. Second, it focused on multimodal data and analyzed detection methods based on audio-visual feature fusion and spatiotemporal alignment, as well as cross-modal detection methods based on vision-language pre-trained models. Next, it introduced commonly used datasets for violent behavior detection and compared the performance of existing methods. Finally, it summarized the current problems and future research directions.

Foundation Support

福建省自然科学基金面上项目(2026J001984)
福建省中青年教师教育科研项目(科技类)(JAT210266)

Publish Information

DOI: 10.19734/j.issn.1001-3695.2026.05.0135
Publish at: Application Research of Computers Accepted Paper, Vol. 44, 2027 No. 1

Publish History

[2026-08-27] Accepted Paper

Cite This Article

朱月秀, 卿德鹏, 郑艺峰. 弱监督暴力行为检测研究综述 [J]. 计算机应用研究, 2027, 44 (1). (2026-09-14). https://doi.org/10.19734/j.issn.1001-3695.2026.05.0135. (Zhu Yuexiu, Qing Depeng, Zheng Yifeng. Survey on weakly-supervised violent behavior detection [J]. Application Research of Computers, 2027, 44 (1). (2026-09-14). https://doi.org/10.19734/j.issn.1001-3695.2026.05.0135. )

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  • 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.

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