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Spatiotemporal collaborative filter and proxy sparsity learning for event-based person re-identification

Chen Wanzhang
Kong Jun
School of Internet of Things Engineering, Jiangnan University, Wuxi Jiangsu 214122, China

Abstract

To address the challenges of event stream noise and inter-class imbalance in event-based person re-Identification (Event-based ReID) , this paper proposed a novel approach (SCF-Net) that integrated a spatiotemporal collaborative filter with proxy sparsity learning. This method comprised two key components: the spatiotemporal collaborative filter and the local proxy sparsity learning module. The spatiotemporal collaborative filter leveraged the spatiotemporal correlations of genuine events to differentiate them from noisy ones, effectively mitigating the impact of noise on the event stream. Meanwhile, the local proxy sparsity learning module explored feature discrepancies among individuals by mapping features to a local proxy domain and enforcing separation between proxies, yielding a well-defined class boundaries in the feature space. Experiments conducted on the Event-ReID dataset demonstrated that SCF-Net model significantly outperforms existing state-of-the-art approaches, achieving a 6.9% increase in mAP and a 4.4% improvement in Rank-1 accuracy.

Foundation Support

国家自然科学基金资助项目(62371209,62371208)

Publish Information

DOI: 10.19734/j.issn.1001-3695.2024.12.0510
Publish at: Application Research of Computers Accepted Paper, Vol. 42, 2025 No. 8

Publish History

[2025-03-21] Accepted Paper

Cite This Article

陈万章, 孔军. 基于时空协同滤波的事件行人重识别 [J]. 计算机应用研究, 2025, 42 (8). (2025-04-17). https://doi.org/10.19734/j.issn.1001-3695.2024.12.0510. (Chen Wanzhang, Kong Jun. Spatiotemporal collaborative filter and proxy sparsity learning for event-based person re-identification [J]. Application Research of Computers, 2025, 42 (8). (2025-04-17). https://doi.org/10.19734/j.issn.1001-3695.2024.12.0510. )

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.


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