PGCNet: patch graph convolutional network for point cloud segmentation of indoor scenes

Author:

Sun Yuliang,Miao YongweiORCID,Chen Jiazhou,Pajarola Renato

Funder

National Natural Science Foundation of China

Natural Science Foundation of Zhejiang Province

Science Foundation of Zhejiang Sci-Tech University

Publisher

Springer Science and Business Media LLC

Subject

Computer Graphics and Computer-Aided Design,Computer Vision and Pattern Recognition,Software

Reference43 articles.

1. Qi, C.R., Su, H., Mo, K., Guibas, L.J.: Pointnet: deep learning on point sets for 3d classification and segmentation. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 652–660 (2017)

2. Li, Y., Bu, R., Sun, M., Wu, W., Di, X., Chen, B.: Pointcnn: convolution on x-transformed points. In: Advances in Neural Information Processing Systems, pp. 820–830 (2018)

3. Guo, Y., Wang, F., Xin, J.: Point-wise saliency detection on 3d point clouds via covariance descriptors. Vis. Comput. 34(10), 1325–1338 (2018)

4. Guo, H., Zhu, D., Mordohai, P.: Correspondence estimation for non-rigid point clouds with automatic part discovery. Vis. Comput. 32(12), 1511–1524 (2016)

5. Wirth, F., Quchl, J., Ota, J.M., Stiller, C.: Pointatme: efficient 3d point cloud labeling in virtual reality. In: IEEE Intelligent Vehicles Symposium, pp. 1693–1698 (2019)

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