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Semantic part segmentation of single-view point cloud

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References

  1. Kalogerakis E, Hertzmann A, Singh K. Learning 3D mesh segmentation and labeling. ACM Trans Graph, 2010, 29: 102

    Article  Google Scholar 

  2. 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

  3. 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

  4. 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

  5. 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

    Article  Google Scholar 

  6. Chang A X, Funkhouser T, Guibas L J, et al. Shapenet: an information-rich 3D model repository. 2015. ArXiv: 1512.03012

  7. van Kaick O, Tagliasacchi A, Sidi O, et al. Prior knowledge for part correspondence. Comput Graph Forum, 2011, 30: 553–562

    Article  Google Scholar 

  8. 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

  9. Rusinkiewicz S, Levoy M. Efficient variants of the ICP algorithm. In: Proceedings of International Conference on 3D Digital Imaging and Modeling, 2001. 145–152

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Acknowledgements

This work was supported by National Natural Science Foundation of China (Grant Nos. 61502023, 61532003).

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Correspondence to Bin Zhou.

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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

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  • DOI: https://doi.org/10.1007/s11432-018-9689-9