Chinese Journal of Liquid Crystals and Displays, Volume. 40, Issue 4, 642(2025)

PMambaIR:panoramic vision state space model for lightweight image super-resolution

Gang YAN1, Ziyi SONG1, and Shuze GENG2、*
Author Affiliations
  • 1School of Artificial Intelligence,Hebei University of Technology,Tianjin 300131,China
  • 2School of Information Science and Technology,Tianjin University of Technology and Education,Tianjin 300222,China
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    References(24)

    [9] GU A, DAO T. Mamba: linear-time sequence modeling with selective state spaces[J/OL]. arXiv, 2312-00752(2023).

    [19] GUPTA A, GU A, BERANT J. Diagonal state spaces are as effective as structured state spaces[C], 1670(2022).

    [20] PEI X H, HUANG T, XU C. EfficientVMamba: Atrous selective scan for light weight visual mamba[J/OL]. arXiv, 2403-09977(2024).

    [21] GU A, GOEL K, RÉ C. Efficiently modeling long sequences with structured state spaces[C], 1-27(2022).

    [22] NGUYEN E, GOEL K, GU A et al. S4ND: modeling images and videos as multidimensional signals using state spaces[C], 206(2022).

    [23] LIU Y, TIAN Y J, ZHAO Y Z et al. VMamba: visual state space model[J/OL]. arXiv, 2401-10166(2024).

    [24] ZHU L H, LIAO B C, ZHANG Q et al. Vision mamba: efficient visual representation learning with bidirectional state space model[C], 1-14(2024).

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    Gang YAN, Ziyi SONG, Shuze GENG. PMambaIR:panoramic vision state space model for lightweight image super-resolution[J]. Chinese Journal of Liquid Crystals and Displays, 2025, 40(4): 642

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    Paper Information

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    Received: Aug. 22, 2024

    Accepted: --

    Published Online: May. 21, 2025

    The Author Email: Shuze GENG (gengshuze@tute.edu.cn)

    DOI:10.37188/CJLCD.2024-0246

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