Chinese Journal of Liquid Crystals and Displays, Volume. 38, Issue 10, 1434(2023)

Optical flow estimation via fusing sequence image intensity correlation information

Tong AN1, Di JIA1,2、*, Jia-bao ZHANG1, and Peng CAI1
Author Affiliations
  • 1College of Electronic and Information Engineering,Liaoning Technical University,Huludao 125105,China
  • 2College of Electrical and Control Engineering,Liaoning Technical University,Huludao 125105,China
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    References(21)

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    [13] YANG G S, RAMANAN D. Volumetric correspondence networks for optical flow[C], 72(2019).

    [16] AMOS B, KOLTER J Z. OptNet: differentiable optimization as a layer in neural networks[C], 136-145(2017).

    [17] AGRAWAL A, AMOS B, BARRATT S et al. Differentiable convex optimization layers[C], 858(2019).

    [21] WANG J Y, ZHONG Y R, DAI Y C et al. Displacement-invariant matching cost learning for accurate optical flow estimation[C], 1276(2020).

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    Tong AN, Di JIA, Jia-bao ZHANG, Peng CAI. Optical flow estimation via fusing sequence image intensity correlation information[J]. Chinese Journal of Liquid Crystals and Displays, 2023, 38(10): 1434

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    Paper Information

    Category: Research Articles

    Received: Nov. 18, 2022

    Accepted: --

    Published Online: Oct. 25, 2023

    The Author Email: Di JIA (1319423118@qq.com)

    DOI:10.37188/CJLCD.2022-0384

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