Accurate 3D shape representation is essential in engineering applications such as design, optimization, and simulation. In practice, engineering workflows require structured, part-based representations, as objects are inherently designed as assemblies of distinct components. However, most existing methods either model shapes holistically or decompose them without predefined part structures, limiting their applicability in real-world design tasks. We propose PartSDF, a supervised implicit representation framework that explicitly models composite shapes with independent, controllable parts while maintaining shape consistency. Thanks to its simple but innovative architecture, PartSDF outperforms both supervised and unsupervised baselines in reconstruction and generation tasks. We further demonstrate its effectiveness as a structured shape prior for engineering applications, enabling precise control over individual components while preserving overall coherence. Code available at https://github.com/cvlab-epfl/PartSDF.

翻译：精确的三维形状表示在工程设计、优化与仿真等工程应用中至关重要。实践中，工程流程需要结构化、基于部件的表示，因为物体本质上被设计为不同组件的装配体。然而，现有方法大多将形状整体建模，或将其分解为无预定义部件结构的部分，这限制了它们在实际设计任务中的适用性。我们提出了PartSDF，一种监督式隐式表示框架，能够显式地建模具有独立、可控部件且保持形状一致性的复合形状。得益于其简洁而创新的架构，PartSDF在重建与生成任务中均优于监督式和无监督式基线方法。我们进一步证明了其作为工程应用的结构化形状先验的有效性，能够在保持整体一致性的同时实现对单个组件的精确控制。代码发布于 https://github.com/cvlab-epfl/PartSDF。