English(EN) Metric--Phase Fields: Decoupling Distance and Sign for Thin-Structure Reconstruction from Unoriented Point Clouds

新的 Metric--Phase Fields 改进了薄结构的 3D 重建

作者 PulseAugur 编辑部 · [1 个来源] · 2026-05-26 04:00

研究人员开发了一种名为 Metric--Phase Fields (MPFs) 的新方法，以改进从无定向点云中重建薄结构。与现有方法在处理薄或开放几何形状时遇到的困难不同，MPFs 将距离和相位信息解耦。这使得能够更忠实地保留薄层状形状，同时实现更稳健的训练和可靠的表面提取。 AI

影响引入了一种新颖的 3D 重建表示方法，有可能提高使用点云数据的应用程序的细节和鲁棒性。

排序理由这是一篇描述新技术的学术论文。[lever_c_demoted from research: ic=1 ai=1.0]

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arXiv cs.CV TIER_1 English(EN) · Jiayi Kong, Xuhui Chen, Chen Zong, Fei Hou, Junhui Hou, Wenping Wang, Ying He · 2026-05-26 04:00

Metric--Phase Fields：从无定向点云中解耦距离和符号以进行薄结构重建

arXiv:2605.25503v1 Announce Type: new Abstract: Neural Signed Distance Functions (SDFs) excel at reconstructing watertight manifolds but fail on thin structures and open boundaries due to strict inside--outside constraints. Conversely, Unsigned Distance Fields (UDFs) accommodate …