Technology of Graphic & Image
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App. Res. of Comp. Printed Article
Vol. 43, 2026 No. 3
954-960

FDR-Net:human motion prediction combining dynamic graph convolution and frequency-domain reasoning

Jia Wenbo
Zhang Sunjie
School of Optical-Electrical & Computer Engineering, University of Shanghai for Science & Technology, Shanghai 200093, China
DOI: 10.19734/j.issn.1001-3695.2025.05.0223

Abstract

With the rapid development of embodied intelligence and human-computer interaction technologies, accurate prediction of human motion intent becomes crucial for enhancing interaction naturalness and safety. To address the limitations of existing graph convolution-based human motion prediction methods in capturing spatio-temporal features and modeling long-term dependencies, this study proposed a human motion prediction method integrating dynamic graph convolution with frequency domain reasoning. The algorithm firstly designed a multi-hop maximal relative graph convolution to enhance the capability of capturing local motion patterns, combined with reparameterized conditional positional encoding to achieve position awareness. Secondly, it introduced a temporal-aware attention mechanism to model inter-frame dependencies. Finally, the method constructed a frequency-domain graph network to perform multi-scale motion feature reasoning in the frequency domain through Fourier transform. Comparative experiments on the Human3.6M and 3DPW datasets demonstrate that the proposed method achieves significantly lower average displacement error compared to state-of-the-art approaches, generating predictions closer to ground truth. These results verify that the integration of dynamic graph convolution and frequency-domain reasoning effectively enhances the accuracy and long-term stability of human motion prediction, providing technical support for natural and safe human-computer interaction.

Foundation Support

国家自然科学基金资助项目(61603255)
上海市晨光计划资助项目(18CG52)

Publish Information

DOI: 10.19734/j.issn.1001-3695.2025.05.0223
Publish at: Application Research of Computers Printed Article, Vol. 43, 2026 No. 3
Section: Technology of Graphic & Image
Pages: 954-960
Serial Number: 1001-3695(2026)03-038-0954-07

Publish History

[2026-03-05] Printed Article

Cite This Article

贾文博, 张孙杰. FDR-Net:融合动态图卷积与频域推理的人体运动预测 [J]. 计算机应用研究, 2026, 43 (3): 954-960. (Jia Wenbo, Zhang Sunjie. FDR-Net:human motion prediction combining dynamic graph convolution and frequency-domain reasoning [J]. Application Research of Computers, 2026, 43 (3): 954-960. )

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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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