Infrared and Laser Engineering, Volume. 54, Issue 7, 20250189(2025)

Deep learning empowers generation and presentation of virtual-real fusion scenarios in holographic metaverse: development and prospects (invited)

Zehao HE1, Yunhui GAO2, Liangcai CAO2, and Yan ZHANG1、*
Author Affiliations
  • 1Department of Physics, Capital Normal University, Beijing 100048, China
  • 2Department of Precision Instrument, Tsinghua University, Beijing 100084, China
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    Figures & Tables(7)
    (a) Architecture diagram of 3D holographic video communication system; (b) 3D acquisition terminal constructed using structured light camera and light field camera; (c) 3D display terminal constructed using computer-generated holography[5]
    (a) Architecture diagram of the model-driven hologram generation network: Holo-Encoder[32]; (b) Architecture diagram of the model-driven hologram generation network: 4 K-DMDNet[33]
    (a) Schematic diagram of supervised monocular depth estimation; (b) Schematic diagram of unsupervised monocular depth estimation
    (a) Two-stage monocular depth estimation; (b) Feature distillation-based monocular depth estimation; (c) Transfer learning-based monocular depth estimation
    (a) Schematic of data-driven hologram generation; (b) Schematic of model-driven hologram generation
    (a) Generation of broadband holograms; (b) Optimization of initial conditions and solution paths for ill-posed inverse problems
    Gradient variation in the depth direction of holographic recon-structions under initial conditions without and with random phase
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    Zehao HE, Yunhui GAO, Liangcai CAO, Yan ZHANG. Deep learning empowers generation and presentation of virtual-real fusion scenarios in holographic metaverse: development and prospects (invited)[J]. Infrared and Laser Engineering, 2025, 54(7): 20250189

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    Paper Information

    Category: Special issue—Advanced display technology and applications

    Received: Mar. 25, 2025

    Accepted: --

    Published Online: Aug. 29, 2025

    The Author Email: Yan ZHANG (yzhang@cnu.edu.cn)

    DOI:10.3788/IRLA20250189

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