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    • Lightweight Image Super-Resolution Network with Sparse and Permuted Self-Attention

    • In the field of computer vision, researchers have designed the lightweight image super-resolution network SPSANet, which effectively integrates global and local features to improve image clarity.
    • Pages: 1-13(2026)   

      Received:23 October 2025

      Revised:2025-12-19

      Accepted:05 January 2026

      Published Online:06 January 2026

    • DOI: 10.11834/jig.250519     

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  • Wu Siqi, Liu Wei, Chen Weidong. Lightweight Image Super-Resolution Network with Sparse and Permuted Self-Attention[J/OL]. Journal of Image and Graphics, 2026, 1-13. DOI: 10.11834/jig.250519.
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相关作者

Li Yan 南京信息工程大学计算机学院
Dong Shihao 南京信息工程大学计算机学院
Zhang Jiawei 南京信息工程大学计算机学院
Zhao Ru 西北大学新闻传播学院
Zheng Yuhui 南京信息工程大学计算机学院
Bi Xiuping 武汉大学计算机学院国家多媒体软件工程技术研究中心
Chen Shi 武汉大学计算机学院国家多媒体软件工程技术研究中心
Zhang Lefei 武汉大学计算机学院国家多媒体软件工程技术研究中心;湖北珞珈实验室

相关机构

School of Computer Science, Nanjing University of Information Science and Technology
School of Journalism and Communication, Northwest University
National Engineering Research Center for Multimedia Software, School of Computer Science, Wuhan University
Hubei Luojia Laboratory
School of Computer Science and Technology, Harbin Institute of Technology
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