| [1] | Osada R, Funkhouser T, Chazelle B, et al. Shape distributions [J]. ACM Transactions on Graphics (TOG), 2002, 21(4): 807-832. doi: 10.1145/571647.571648 |
| [2] | Sun J, Ovsjanikov M, Guibas L. A concise and provably informative multiscale signature based on heat diffusion[C]//Computer graphics forum. Oxford, UK: Blackwell Publishing Ltd, 2009, 28(5): 1383-1392. |
| [3] | Krizhevsky A, Sutskever I, Hinton G E. ImageNet classification with deep conv neural networks [J]. Communications of the ACM, 2017, 60(6): 84-90. doi: 10.1145/3065386 |
| [4] | Pan X Z, Zhang S Q, Guo W P. Application of multi-mode deep convolutional neural network to video expression recognition [J]. Optics and Precision Engineering, 2019, 27(4): 230-237. (in Chinese) |
| [5] | 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 (CVPR), 2017: 77-85. |
| [6] | Qi C R, Li Y, Hao S, et al. PointNet++: Deep hierarchical feature learning on point sets in a metric space[C]//Advances in Neural Information Processing Systems, 2017, 30: 5099-5108. |
| [7] | Li Y, Bu R, Sun M, et al. Pointcnn: Convolution on X-transformed points[C]//Advances in Neural Information Process ing Systems, 2018, 31: 820-830. |
| [8] | Wang Y, Sun Y, Liu Z, et al. Dynamic graph CNN for learning on point clouds [J]. ACM Transactions on Graphics (TOG), 2019, 38(5): 1-12. |
| [9] | Jaderberg M, Simonyan K, Zisserman A. Spatial transformer networks[C]//Advances in Neural Information Processing Systems, 2015, 28: 2017-2025. |
| [10] | Hastie T, Tibshirani R. Discriminant adaptive nearest neighbor classification and regression[C]//Advances in Neural Information Processing Systems, 1996, 9: 409-415. |
| [11] | Jégou H, Douze M, Schmid C, et al. Aggregating local descriptors into a compact image representation[C]//2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition. IEEE, 2010: 3304-3311. |
| [12] | Yu F, Koltun V. Multi-scale context aggregation by dilated convolutions [J]. arXiv preprint arXiv, 2015: 1511.07122. |
| [13] | Wu Z, Song S, Khosla A, et al. 3 D ShapeNets: A deep representation for volumetric shapes[C]//Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2015: 1912-1920. |
| [14] | Yi L, Guibas L, Hertzmann A, et al. Learning hierarchical shape segmentation and labeling from online repositories [J]. ACM Transactions on Graphics, 2017, 36(4): 1-12. |
| [15] | Zhang D, He F, Tu Z, et al. Pointwise geometric and semantic learning network on 3 D point clouds [J]. Integrated Computer-Aided Engineering, 2020, 27(1): 57-75. |
| [16] | Duan Y, Zheng Y, Lu J, et al. Structural relational reasoning of point clouds[C]//Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2019: 949-958. |
| [17] | Li D, Shen X, Yu Y, et al. GGM-net: Graph geometric moments convolution neural network for point cloud shape classification[C]//IEEE Access, 2020, 8: 124989-124998. |
| [18] | Zhai Z, Zhang X, Yao L. Multi-scale dynamic graph convolution network for point clouds classification[C]//IEEE Access, 2020, 8: 65591-65598. |
| [19] | Lyu Y, Huang X, Zhang Z. EllipsoidNet: Ellipsoid representation for point cloud classification and segmentation [J]. arXiv preprint arXiv, 2021: 2103.02517. |