Laser & Optoelectronics Progress, Volume. 61, Issue 16, 1611006(2024)

Dynamic Light Field Reconstruction Based on Gradient Descent Deep Equilibrium Model (Invited)

Ruixue Wang1, Xue Wang1, Guoqing Zhou1, Zhaolin Xiao2, and Qing Wang1、*
Author Affiliations
  • 1School of Computer Science, Northwestern Polytechnical University, Xi'an 710072, Shaanxi, China
  • 2School of Computer Science and Engineering, Xi'an University of Technology, Xi'an 710048, Shaanxi, China
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    References(43)

    [4] Zhang M, Li J J, Wei J et al. Memory-oriented decoder for light field salient object detection[C], 896-906(2019).

    [13] Fu M X, Zhu X Y, Zhang L et al. Particle field reconstruction in light field particle image velocimetry based on deep residual neural networks[J]. Acta Optica Sinica, 44, 1612001(2024).

    [19] Ng R, Levoy M, Brédif M et al. Light field photography with a hand-held plenoptic camera[D](2005).

    [28] Wakin M B, Laska J N, Duarte M F et al. Compressive imaging for video representation and coding[C](2006).

    [39] Bai S, Kolter J Z, Koltun V. Deep equilibrium models[C], 47-59(2019).

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    Ruixue Wang, Xue Wang, Guoqing Zhou, Zhaolin Xiao, Qing Wang. Dynamic Light Field Reconstruction Based on Gradient Descent Deep Equilibrium Model (Invited)[J]. Laser & Optoelectronics Progress, 2024, 61(16): 1611006

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    Paper Information

    Category: Imaging Systems

    Received: May. 31, 2024

    Accepted: Jul. 15, 2024

    Published Online: Aug. 12, 2024

    The Author Email: Qing Wang (qwang@nwpu.edu.cn)

    DOI:10.3788/LOP241400

    CSTR:32186.14.LOP241400

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