Interlaced Fiber Construction: A Topology-First Framework for Generative 3D Modeling Through Weaving and Winding
Abstract
Existing 3D generative methods commonly represent objects using implicit neural fields, point clouds, volumetric distributions, polygonal surfaces, or collections of Gaussian primitives. Although these representations support diverse forms of 3D synthesis, they do not inherently encode the construction logic of objects assembled from continuous strands, fibers, filaments, wires, or ribbons. This paper proposes Interlaced Fiber Construction (IFC), a topology-first framework for generative 3D modeling in which an object is constructed from interacting elongated elements rather than generated directly as a monolithic surface. IFC represents each construction element through a continuous spatial trajectory, a cross-sectional profile, material attributes, and a set of topological relations with other elements. A generative controller jointly determines element placement, interlacing sequences, winding paths, attachment relations, and geometric adjustments. A topology-constrained optimization process then refines the construction while penalizing unintended intersections, excessive curvature, material overlap, and violations of prescribed structural constraints. The framework is designed to support woven, braided, wound, knotted, and hybrid structures, including open lattices and hollow objects. Unlike approaches that focus primarily on surface reconstruction or visual appearance, IFC explicitly treats the relationships among construction elements as part of the generative state. This paper formalizes the proposed representation, generation procedure, objective functions, and evaluation protocol. Because the framework has not yet been empirically validated, no quantitative performance improvements are claimed. Its principal research hypothesis is that explicitly modeling construction topology alongside continuous geometry can improve structural controllability, editability, and physical plausibility in generative 3D modeling.
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BibTeX
@misc{zhang2026interlaced,
title = {{Interlaced Fiber Construction: A Topology-First Framework for Generative 3D Modeling Through Weaving and Winding}},
author = {Jincheng Zhang},
howpublished = {Zenodo},
year = {2026},
month = oct,
doi = {10.5281/zenodo.23636292},
url = {https://zenodo.org/records/23636292},
note = {CC BY 4.0},
}
RIS
TY - UNPB
TI - Interlaced Fiber Construction: A Topology-First Framework for Generative 3D Modeling Through Weaving and Winding
AU - Jincheng Zhang
PY - 2026
DA - 2026/10/25
PB - Zenodo
DO - 10.5281/zenodo.23636292
UR - https://zenodo.org/records/23636292
AB - Existing 3D generative methods commonly represent objects using implicit neural fields, point clouds, volumetric distributions, polygonal surfaces, or collections of Gaussian primitives. Although these representations support diverse forms of 3D synthesis, they do not inherently encode the construction logic of objects assembled from continuous strands, fibers, filaments, wires, or ribbons. This paper proposes Interlaced Fiber Construction (IFC), a topology-first framework for generative 3D modeling in which an object is constructed from interacting elongated elements rather than generated directly as a monolithic surface. IFC represents each construction element through a continuous spatial trajectory, a cross-sectional profile, material attributes, and a set of topological relations with other elements. A generative controller jointly determines element placement, interlacing sequences, winding paths, attachment relations, and geometric adjustments. A topology-constrained optimization process then refines the construction while penalizing unintended intersections, excessive curvature, material overlap, and violations of prescribed structural constraints. The framework is designed to support woven, braided, wound, knotted, and hybrid structures, including open lattices and hollow objects. Unlike approaches that focus primarily on surface reconstruction or visual appearance, IFC explicitly treats the relationships among construction elements as part of the generative state. This paper formalizes the proposed representation, generation procedure, objective functions, and evaluation protocol. Because the framework has not yet been empirically validated, no quantitative performance improvements are claimed. Its principal research hypothesis is that explicitly modeling construction topology alongside continuous geometry can improve structural controllability, editability, and physical plausibility in generative 3D modeling.
ER -