Laser & Infrared, Volume. 55, Issue 1, 40(2025)

Point cloud semantic segmentation based on feature expansion and separation pooling

CHEN Chong-ming1, YU Jin-xing2, HAN Lu3, WANG Hao-ran3, ZHANG Dian-mao4, and CHEN Qi4
Author Affiliations
  • 1State Grid Hebei Electric Power Research Institute, Shijiazhuang 050021, China
  • 2State Grid Hebei Energy Technology Service Co., Ltd., Shijiazhuang 050021, China
  • 3State Grid Hebei Construction Company, Shijiazhuang 050030, China
  • 4Unis Software System Co., Ltd., Beijing 100084, China
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    References(8)

    [2] [2] Nardinocchi C, Balsi M, Esposito S. Fully automatic point cloud analysis for powerline corridor mapping[J]. IEEE Transactions on Geoscience and Remote Sensing, 2020, (99): 1-12.

    [3] [3] Zhang C, Chen C, Hu Q, et al. Efficient segmentation and thresholding approach for power line extraction in urban areas[J]. Front. Earth Sci., 2018, 12: 102-113.

    [4] [4] Hu W, Liu J, Zou Q. A robust power-line extraction method from LiDAR point clouds using graph cut based on the normalized cut (NCut) criterion[J]. ISPRS Journal of Photogrammetry and Remote Sensing, 2019, 147: 86-99.

    [5] [5] Zhu Q, Tian D, Shen J, et al. (2020). Semantic segmentation of power line point cloud based on feature clustering and region growing[C]//2020 2nd International Conference on Geomatics and System Engineering, IEEE, 2020: 689-693.

    [8] [8] Qi C R, Su H, Mo K, et al. Pointnet: deep learning on point sets for 3D classification and segmentation[C]//Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2017: 652-660.

    [9] [9] Li J, Chen B M, Lee G H. So-net: Self-organizing network for point cloud analysis[C]//Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2018: 9397-9406.

    [11] [11] Li Y, Bu R, Sun M, et al. PointCNN: convolution on -transformed points[C]//Neural Information Processing Systems, Curran Associates Inc, 2018.

    [12] [12] Hu Q, Yang B, Xie L, et al. R and LA-Net: efficient semantic segmentation of large-scale point clouds[C]//Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recogni-tion, 2020: 11108-11117.

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    CHEN Chong-ming, YU Jin-xing, HAN Lu, WANG Hao-ran, ZHANG Dian-mao, CHEN Qi. Point cloud semantic segmentation based on feature expansion and separation pooling[J]. Laser & Infrared, 2025, 55(1): 40

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    Paper Information

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    Received: Apr. 18, 2024

    Accepted: Mar. 13, 2025

    Published Online: Mar. 13, 2025

    The Author Email:

    DOI:10.3969/j.issn.1001-5078.2025.01.006

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