Laser & Infrared, Volume. 54, Issue 2, 185(2024)
Point cloud semantic segmentation considering multi-scale supervision
[3] [3] Kirillov A, Wu Y, He K, et al. Pointrend: Image segmentation as rendering[C]//Proceedings of the IEEE/CVF conference on computer vision and pattern recognition, 2020: 9799-9808.
[4] [4] Huang H, Lin L, Tong R, et al. Unet 3+: a full-scale connected unet for medical image segmentation[C]//ICASSP 2020-2020 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2020: 1055-1059.
[5] [5] Xu J, Gong J, Zhou J, et al. Scene encoder: scene-aware semantic segmentation of point clouds with a learnable scene descriptor[C]//Proceedings of the Twenty-Ninth International Conference on International Joint Conferences on Artificial Intelligence, 2021: 601-607.
[6] [6] Ahn P, Yang J, Yi E, et al. Projection-based point convolution for efficient point cloud segmentation[J]. IEEE Access, 2022, 10: 15348-15358.
[7] [7] Kellner M, Stahl B, Reiterer A. Fused projection-based point cloud segmentation[J]. Sensors, 2022, 22(3): 1139.
[8] [8] Meng H Y, Gao L, Lai Y K, et al. Vv-net: voxel vae net with group convolutions for point cloud segmentation[C]//Proceedings of the IEEE/CVF International Conference on Computer Vision, 2019: 8500-8508.
[9] [9] Zhao L, Xu S, Liu L, et al. SVASeg: sparse voxel-based attention for 3D LiDAR point cloud semantic segmentation[J]. Remote Sensing, 2022, 14(18): 4471.
[10] [10] 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.
[11] [11] Qi C R, Yi L, Su H, et al. Pointnet++: deep hierarchical feature learning on point sets in a metric space[J]. Advances in Neural Information Processing Systems, 2017, 30.
[12] [12] Zhao H, Jiang L, Fu C W, et al. Point web: enhancing local neighborhood features for point cloud processing[C]//2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2019: 5560-5568.
[13] [13] Fan S, Dong Q, Zhu F, et al. SCF-net: learning spatial contextual features for large-scale point cloud segmentation[C]//2021 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021: 14499-14508.
[15] [15] Zhou Z, Rahman Siddiquee M M, Tajbakhsh N, et al. Unet++: a nested u-net architecture for medical image segmentation[C]//Deep Learning in Medical Image Analysis and Multimodal Learning for Clinical Decision Support: 4th International Workshop, DLMIA 2018, and 8th International Workshop, 2018: 3-11.
[16] [16] Gong J, Xu J, Tan X, et al. Omni-supervised point cloud segmentation via gradual receptive field component reasoning[C]//2021 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021: 11668-11677.
[17] [17] Huang Q, Wang W, Neumann U. Recurrent slice networks for 3D segmentation of point clouds[C]//2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2018: 2626-2635.
[18] [18] Landrieu L, Simonovsky M. Large-scale point cloud semantic segmentation with superpoint graphs[C]//Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2018: 4558-4567.
[19] [19] Li Y Y, Bu R, Sun M C, et al. PointCNN: convolution on X -transformed points[C]//32nd Conference on Neural Information Processing Systems (NIPS), 2018.
[20] [20] Hu Q, Yang B, Xie L, et al. RandLA-net: efficient semantic segmentation of large-scale point clouds[C]//2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2020: 11105-11114.
[21] [21] Thomas H, Qi C R, Deschaud J-E, et al. Kpconv: flexible and deformable convolution for point clouds[C]//Proceedings of the IEEE/CVF International Conference on Computer Vision, 2019: 6411-6420.
[22] [22] Shuai H, Xu X, Liu Q. Backward attentive fusing network with local aggregation classifier for 3D point cloud semantic segmentation[J]. IEEE Trans Image Process, 2021, 30: 4973-4984.
[23] [23] Milioto A, Vizzo I, Behley J, et al. Rangenet++: fast and accurate lidar semantic segmentation[C]//2019 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2019: 4213-4220.
[24] [24] Zhang Y, Zhou Z, David P, et al. Polarnet: an improved grid representation for online lidar point clouds semantic segmentation[C]//Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2020: 9601-9610.
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WEN Yang-Hui, YANG Xiao-wen, ZHANG Yuan, HAN Xie, KUANG Li-qun, XUE Hong-xin. Point cloud semantic segmentation considering multi-scale supervision[J]. Laser & Infrared, 2024, 54(2): 185
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Received: Apr. 4, 2023
Accepted: Jun. 4, 2025
Published Online: Jun. 4, 2025
The Author Email: YANG Xiao-wen (wenyang1314@nuc.edu.cn)