References
Kalogerakis E, Hertzmann A, Singh K. Learning 3D mesh segmentation and labeling. ACM Trans Graph, 2010, 29: 102
Charles R Q, Su H, Kaichun M, et al. Pointnet: deep learning on point sets for 3D classification and segmentation. In: Proceedings of IEEE Conference on Computer Vision and Pattern Recognition (CVPR), Honolulu, 2017. 77–85
Qi C R, Li Y, Su H, et al. PointNet++: deep hierarchical feature learning on point sets in a metric space. In: Proceedings of the 31st Conference on Neural Information Processing Systems, 2017. 1–10
Li Y Y, Bu R, Sun M C, et al. PointCNN: convolution on X-transformed points. In: Proceedings of the 32nd Conference on Neural Information Processing Systems, 2018. 1–11
Chen D Y, Tian X P, Shen Y T, et al. On visual similarity based 3D model retrieval. Comput Graph Forum, 2003, 22: 223–232
Chang A X, Funkhouser T, Guibas L J, et al. Shapenet: an information-rich 3D model repository. 2015. ArXiv: 1512.03012
van Kaick O, Tagliasacchi A, Sidi O, et al. Prior knowledge for part correspondence. Comput Graph Forum, 2011, 30: 553–562
Kalogerakis E, Averkiou M, Maji S, et al. 3D shape segmentation with projective convolutional networks. In: Proceedings of the IEEE Computer Vision and Pattern Recognition (CVPR), 2017. 6630–6639
Rusinkiewicz S, Levoy M. Efficient variants of the ICP algorithm. In: Proceedings of International Conference on 3D Digital Imaging and Modeling, 2001. 145–152
Acknowledgements
This work was supported by National Natural Science Foundation of China (Grant Nos. 61502023, 61532003).
Author information
Authors and Affiliations
Corresponding author
Supplementary Materials
Rights and permissions
About this article
Cite this article
Peng, H., Zhou, B., Yin, L. et al. Semantic part segmentation of single-view point cloud. Sci. China Inf. Sci. 63, 224101 (2020). https://doi.org/10.1007/s11432-018-9689-9
Received:
Accepted:
Published:
DOI: https://doi.org/10.1007/s11432-018-9689-9