[33] Ishit Mehta, Michael Gharbi, Connelly Barnes, Eli Shechtman, Ravi Ramamoorthi, and Mamohan Chandraker. Modulated periodic activations for generalizable local functional representations. In Proceedings of the IEEE/CVF International Conference on Computer Vision (ICCV), 2021.
[34] Lars Mescheder, Michael Oechsle, Michael Niemeyer, Sebastian Nowozin, and Andreas Geiger. Occupancy networks: Learning 3d reconstruction in function space. In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2019.
[35] Michael Oechsle, Songyou Peng, and Andreas Geiger. Unisurf: Unifying neural implicit surfaces and radiance fields for multi-view reconstruction. In International Conference on Computer Vision (ICCV), 2021.
[36] Barrett O'Neill. Chapter 5 - shape operators. In Barrett O'Neill, editor, Elementary Differential Geometry (Second Edition), pages 202-262. Academic Press, Boston, second edition edition, 2006.
[37] Jeong Joon Park, Peter Florence, Julian Straub, Richard Newcombe, and Steven Lovegrove. Deepsdf: Learning continuous signed distance functions for shape representation. In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2019.
[38] Songyou Peng, Chiyu "Max" Jiang, and Yiyi Liao. Shape As Points: a differentiable poisson solver. In Advances in Neural Information Processing Systems (NeurIPS), 2021.
[39] C. Schroers, S. Setzer, and J. Weickert. A variational taxonomy for surface reconstruction from oriented points. Computer Graphics Forum, 33(5):195-204, 2014.
[40] Vincent Sitzmann, Julien N.P. Martel, Alexander W. Bergman, David B. Lindell, and Gordon Wetzstein. Implicit neural representations with periodic activation functions. In Advances in Neural Information Processing Systems (NeurIPS), 2020.
[41] Peng Songyou, Niemeyer Michael, Mescheder Lars, Pollefeys Marc, and Andreas Geiger. Convolutional occupancy networks. In Proceedings of the European Conference on Computer Vision (ECCV), 2020.
[42] Raphael Sulzer, Loic Landrieu, Renaud Marlet, and Bruno Vallet. A survey and benchmark of automatic surface reconstruction from point clouds, 2023.
[43] Matthew Tancik, Vincent Casser, Xinchen Yan, Sabeek Pradhan, Ben Mildenhall, Pratul P Srinivasan, Jonathan T Barron, and Henrik Kretzschmar. Block-nerf: Scalable large scene neural view synthesis. In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, pages 8248–8258, 2022.
[44] Jia-Heng Tang, Weikai Chen, jie Yang, Bo Wang, Songrun Liu, Bo Yang, and Lin Gao. OctField: Hierarchical Implicit Functions for 3D Modeling. In Advances in Neural Information Processing Systems (NeurIPS), 2021.
[45] Peng Wang, Lingjie Liu, Yuan Liu, Christian Theobalt, Taku Komura, and Wenping Wang. Neus: Learning neural implicit surfaces by volume rendering for multi-view reconstruction. NeurIPS, 2021.
[46] Peng-Shuai Wang, Yang Liu, and Xin Tong. Dual octree graph networks for learning adaptive volumetric shape representations. ACM Trans. Graph., 41(4), 2022.
[47] Pengfei Wang, Zixiong Wang, Shiqing Xin, Xifeng Gao, Wenping Wang, and Changhe Tu. Restricted delaunay triangulation for explicit surface reconstruction. ACM Trans. Graph., 41(5), oct 2022.
[48] Zixiong Wang, Pengfei Wang, Pengshuai Wang, Qiujie Dong, Junjie Gao, Shuangmin Chen, Shiqing Xin, Changhe Tu, and Wenping Wang. Neural-imls: Self-supervised implicit moving least-squares network for surface reconstruction, 2022.