Optics and Precision Engineering, Volume. 32, Issue 12, 1941(2024)

Part segmentation method of point cloud considering optimal allocation and optimal mask

Xijiang CHEN1...2,3, Xi SUN2,*, Bufan ZHAO2, Qing AN1 and Xianquan HAN4 |Show fewer author(s)
Author Affiliations
  • 1School of Artificial Intelligence, Wuchang University of Technology, Wuhan430223,China
  • 2School of Safety Science and Emergency Management, Wuhan University of Technology, Wuhan430070,China
  • 3Key Laboratory of Mine Environmental Monitoring and Improving around Poyang Lake of Ministry of Natural Resources, East China University of Technology, Nanchang001,China
  • 4Changjiang River Scientific Research Institute of Changjiang Water Resources Commission, Wuhan30019,China
  • show less
    References(34)

    [1] R Q CHARLES, S HAO, K C MO et al. PointNet: deep learning on point sets for 3D classification and segmentation, 77-85(2017).

    [3] Y WANG, Y B SUN, Z W LIU et al. Dynamic graph CNN for learning on point clouds. ACM Transactions on Graphics, 38, 1-12(2019).

    [4] Y LI, R BU, M SUN et al. PointCNN: Convolution on Χ-transformed points, 31(2018).

    [5] Y R SHEN, C FENG, Y Q YANG et al. Mining point cloud local structures by kernel correlation and graph pooling, 4548-4557(2018).

    [6] W X WU, Z A QI, F X LI. PointConv: deep convolutional networks on 3D point clouds, 9613-9622(2019).

    [7] H THOMAS, C R QI, J E DESCHAUD et al. KPConv: flexible and deformable convolution for point clouds, 6410-6419(2019).

    [8] M T XU, R Y DING, H S ZHAO et al. PAConv: position adaptive convolution with dynamic kernel assembling on point clouds, 3172-3181(2021).

    [9] A HALEVY, P NORVIG, F PEREIRA. The unreasonable effectiveness of data. IEEE Intelligent Systems, 24, 8-12(2009).

    [10] C SUN, A SHRIVASTAVA, S SINGH et al. Revisiting unreasonable effectiveness of data in deep learning era, 843-852(2017).

    [11] Y Chen, V T Hu, E Gavves et al. Pointmixup: augmentation for point clouds, 330-345(28).

    [12] A KRIZHEVSKY, I SUTSKEVER, G E HINTON. ImageNet classification with deep convolutional neural networks. Communications of the ACM, 60, 84-90(2017).

    [13] Y LECUN, L BOTTOU, Y BENGIO et al. Gradient-based learning applied to document recognition. Proceedings of the IEEE, 86, 2278-2324(1998).

    [14] F J MORENO-BAREA, F STRAZZERA, J M JEREZ et al. Forward noise adjustment scheme for data augmentation, 728-734(2018).

    [16] H INOUE. Data augmentation by pairing samples for images classification. arXiv preprint(2018).

    [17] Z ZHONG, L ZHENG, G L KANG et al. Random erasing data augmentation. Proceedings of the AAAI Conference on Artificial Intelligence, 34, 13001-13008(2020).

    [21] S YUN, D HAN, S CHUN et al. CutMix: Regularization strategy to train strong classifiers with localizable features, 6022-6031(2019).

    [22] A CRESWELL, T WHITE, V DUMOULIN et al. Generative adversarial networks: an overview. IEEE Signal Processing Magazine, 35, 53-65(2018).

    [24] S V SHESHAPPANAVAR, V V SINGH, C KAMBHAMETTU. PatchAugment: local neighborhood augmentation in point cloud classification, 2118-2127(2021).

    [25] S KIM, S LEE, D HWANG et al. Point cloud augmentation with weighted local transformations, 528-537(2021).

    [26] R H LI, X Z LI, P A HENG et al. PointAugment: an auto-augmentation framework for point cloud classification, 6377-6386(2020).

    [27] J ZHANG, L CHEN, B OUYANG et al. Pointcutmix: Regularization strategy for point cloud classification. Neurocomputing, 505, 58-67(2022).

    [28] D LEE, J LEE, J LEE et al. Regularization strategy for point cloud via rigidly mixed sample, 15895-15904(2021).

    [30] J H KIM, W CHOO, H O SONG. Puzzle Mix: exploiting saliency and local statistics for optimal mixup, 5275-5285(2020).

    [31] S L HUANG, X C WANG, D C TAO. SnapMix: semantically proportional mixing for augmenting fine-grained data, 35, 1628-1636(2021).

    [32] S LEE, M JEON, I KIM et al. Sagemix: saliency-guided mixup for point clouds, 35, 23580-23592(2022).

    [33] C H LEE, A VARSHNEY, D W JACOBS. Mesh saliency, 659-666(2005).

    [34] AX CHANG, T FUNKHOUSER, L GUIBAS et al. ShapeNet: an information-rich 3d model repository. arXiv preprint(2015).

    Tools

    Get Citation

    Copy Citation Text

    Xijiang CHEN, Xi SUN, Bufan ZHAO, Qing AN, Xianquan HAN. Part segmentation method of point cloud considering optimal allocation and optimal mask[J]. Optics and Precision Engineering, 2024, 32(12): 1941

    Download Citation

    EndNote(RIS)BibTexPlain Text
    Save article for my favorites
    Paper Information

    Category:

    Received: Nov. 28, 2023

    Accepted: --

    Published Online: Aug. 28, 2024

    The Author Email: SUN Xi (3022669424@qq.com)

    DOI:10.37188/OPE.20243212.1941

    Topics