PyFRep: Shape Modeling with Differentiable Function Representation

We propose a framework for performing differentiable geometric modeling based on the Function Representation (FRep). The framework is built on top of modern libraries for performing automatic differentiation allowing us to obtain derivatives w.r.t. space or shape parameters. We demonstrate possible applications of this framework: Curvature estimation for shape interrogation, signed distance function computation and approximation and fitting shape parameters of a parametric model to data. Our framework is released as open-source.

Publication Details

Journal
ArXiv.org
Published
2025-04-19
Primary Topic
3D Shape Modeling and Analysis
Type
article
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article

PyFRep: Shape Modeling with Differentiable Function Representation

ArXiv.org
3D Shape Modeling and Analysis
article

PyFRep: Shape Modeling with Differentiable Function Representation

article en

Abstract

We propose a framework for performing differentiable geometric modeling based on the Function Representation (FRep). The framework is built on top of modern libraries for performing automatic differentiation allowing us to obtain derivatives w.r.t. space or shape parameters. We demonstrate possible applications of this framework: Curvature estimation for shape interrogation, signed distance function computation and approximation and fitting shape parameters of a parametric model to data. Our framework is released as open-source.

ArXiv.org
Openalex Percentile: Top 49%
3D Shape Modeling and Analysis
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PyFRep: Shape Modeling with Differentiable Function Representation · ArXiv.org (2025) | TGRS Research Map | TGRS