Unsupervised Decomposition of 3D Shapes into Expressive and Editable Extruded Profile Primitives

摘要

Transforming 3D shapes into representations that support part-level editing, flexible redesign, and efficient compression is vital for asset customization, content creation, and optimization in digital design. Despite its importance, achieving a representation that balances expressivity, editability, compactness, and interpretability remains a challenge. We introduce 3D2EP, a novel method for 3D shape decomposition that represents objects as a collection of differentiable, parametric primitives. Given a 3D shape represented by a voxel grid, 3D2EP decomposes this into a set of primitive parts, each generated by extruding a scaled 2D profile along a 3D curve, with the requisite components being predicted in a feedforward manner. That is, each primitive is constrained to have a single cross-section profile, up to scale. This enables the primitives to adapt to the data, capturing the geometry with precision but without excess degrees-of-freedom that would stymie editability. Extensive evaluations highlight 3D2EP’s ability to reconstruct complex shapes with a compact and interpretable representation, emphasizing its suitability for a wide range of 3D modeling applications.