Laser & Optoelectronics Progress, Volume. 61, Issue 12, 1200003(2024)

Advancements in Semantic Segmentation Methods for Large-Scale Point Clouds Based on Deep Learning

Da Ai1, Xiaoyang Zhang1、*, Ce Xu1, Siyu Qin1, and Hui Yuan2
Author Affiliations
  • 1School of Communications and Information Engineering, Xi'an University of Posts & Telecommunications, Xi'an 710121, Shaanxi, China
  • 2School of Control Science and Engineering, Shandong University, Jinan 250100, Shandong, China
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    References(113)

    [30] Shuang F, Huang X W, Li Y et al. A survey of large-scale point cloud semantic segmentation based on deep learning[J]. Science of Surveying and Mapping, 48, 195-209(2023).

    [31] Lu J, Jia X R, Zhou J et al. A review of deep learning based on 3D point cloud segmentation[J]. Control and Decision, 38, 595-611(2023).

    [59] Charles R Q, Yi L, Su H et al. PointNet++: deep hierarchical feature learning on point sets in a metric space[C], 0599-5108(2017).

    [66] Li Y, Bu R, Sun M et al. Pointcnn: convolution on x-transformed points[C], 828-838(2018).

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    Da Ai, Xiaoyang Zhang, Ce Xu, Siyu Qin, Hui Yuan. Advancements in Semantic Segmentation Methods for Large-Scale Point Clouds Based on Deep Learning[J]. Laser & Optoelectronics Progress, 2024, 61(12): 1200003

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    Paper Information

    Category: Reviews

    Received: Jul. 21, 2023

    Accepted: Sep. 18, 2023

    Published Online: Jun. 5, 2024

    The Author Email: Xiaoyang Zhang (zxy1017254139@163.com)

    DOI:10.3788/LOP231771

    CSTR:32186.14.LOP231771

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