Computing quasiconformal folds
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Abstract (arXiv)
We propose a novel way of computing surface folding maps via solving a linear PDE. This framework is a generalization to the existing quasiconformal methods and allows manipulation of the geometry of folding. Moreover, the crucial quantity that characterizes the geometry occurs as the coefficient of the equation, namely the Beltrami coefficient. This allows us to solve an inverse problem of parametrizing the folded surface given only partial data but with known folding topology. Various interesting applications such as fold sculpting on 3D models and self-occlusion reasoning are demonstrated to show the effectiveness of our method.
Key facts. Cited by 4 papers in the map (data through 14 Oct 2026). First posted on arXiv 11 Apr 2018.
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Citing papers per year: 2021: 1; 2022: 0; 2023: 0; 2024: 1; 2025: 1; 2026: 1.
4 papers.
- 2021A Deep Learning Framework for Diffeomorphic Mapping Problems via Quasi-conformal Geometry applied to Imagingcited by 7
- 2025Free-Boundary Quasiconformal Maps via a Least-squares Operator in Diffeomorphism Optimizationcited by 1
- 2024Deep Learning-Based Quasi-Conformal Surface Registration for Partial 3D Faces Applied to Facial Recognitioncited by 0
- 2026Two-chart Beltrami Optimization for Distortion-Controlled Spherical Bijection with Application to Brain Surface Registrationcited by 0
- 2026Two-chart Beltrami Optimization for Distortion-Controlled Spherical Bijection with Application to Brain Surface Registration2 Feb 2026
- 2025Free-Boundary Quasiconformal Maps via a Least-squares Operator in Diffeomorphism Optimization12 Nov 2025
- 2024Deep Learning-Based Quasi-Conformal Surface Registration for Partial 3D Faces Applied to Facial Recognition16 May 2024
- 2021A Deep Learning Framework for Diffeomorphic Mapping Problems via Quasi-conformal Geometry applied to Imaging20 Oct 2021