用8参数新几何体+迭代拟合，高效生成可编辑的3D模型。
Residual Primitive Fitting of 3D Shapes with SuperFrusta
- 提出SuperFrustum几何体，8参数可表达圆柱、球体等复杂形状。
- 迭代拟合算法在多个数据集上提升IoU超9点，用一半数量的基元。
- 适合需要高保真且可编辑3D建模的设计师和工业应用。
我们提出一种将3D形状转化为紧凑且可编辑的解析基元组合的框架，直接解决重建精度与简洁性之间的长期权衡。方法包含两项核心贡献：一种新型基元SuperFrustum，以及一种迭代拟合算法Residual Primitive Fitting（ResFit）。SuperFrustum具有三大特性：(1) 表达力强，可建模圆柱、球体、锥体及其变形成分；(2) 可编辑，仅需8个参数；(3) 可优化，其符号距离场几乎处处对参数可微。ResFit是一种无监督流程，通过全局分析与局部优化交替进行，迭代拟合未解释残差，为每个输入形状发现既简洁又准确的分解。在多样化的3D基准测试中，本方法达到当前最优性能，IoU提升超过9点，同时使用基元数量仅为先前工作的近一半。生成的组合有效连接密集3D数据与人类可操控设计，产出高保真且可编辑的形状程序。
原文摘要 · Abstract (English)
We introduce a framework for converting 3D shapes into compact and editable assemblies of analytic primitives, directly addressing the persistent trade-off between reconstruction fidelity and parsimony. Our approach combines two key contributions: a novel primitive, termed SuperFrustum, and an iterative fiting algorithm, Residual Primitive Fitting (ResFit). SuperFrustum is an analytical primitive that is simultaneously (1) expressive, being able to model various common solids such as cylinders, spheres, cones & their tapered and bent forms, (2) editable, being compactly parameterized with 8 parameters, and (3) optimizable, with a sign distance field differentiable w.r.t. its parameters almost everywhere. ResFit is an unsupervised procedure that interleaves global shape analysis with local optimization, iteratively fitting primitives to the unexplained residual of a shape to discover a parsimonious yet accurate decompositions for each input shape. On diverse 3D benchmarks, our method achieves state-of-the-art results, improving IoU by over 9 points while using nearly half as many primitives as prior work. The resulting assemblies bridge the gap between dense 3D data and human-controllable design, producing high-fidelity and editable shape programs.
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