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Related papers: Mesh Simplification For Unfolding

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For domains that are easily represented by structured meshes, robust geometric multigrid solvers can quickly provide the numerical solution to many discretized elliptic PDEs. However, for complicated domains with unstructured meshes,…

Numerical Analysis · Mathematics 2025-09-11 Nicolas Nytko , Scott MacLachlan , J. David Moulton , Luke N. Olson , Andrew Reisner , Matthew West

3D reconstruction from 2D images is a central problem in computer vision. Recent works have been focusing on reconstruction directly from a single image. It is well known however that only one image cannot provide enough information for…

Computer Vision and Pattern Recognition · Computer Science 2019-01-25 Jhony K. Pontes , Chen Kong , Anders Eriksson , Clinton Fookes , Sridha Sridharan , Simon Lucey

Polygonal meshes provide an efficient representation for 3D shapes. They explicitly capture both shape surface and topology, and leverage non-uniformity to represent large flat regions as well as sharp, intricate features. This…

Machine Learning · Computer Science 2019-07-03 Rana Hanocka , Amir Hertz , Noa Fish , Raja Giryes , Shachar Fleishman , Daniel Cohen-Or

We address the unsolved problem of unfolding prismatoids in a new context, viewing a "topless prismatoid" as a convex patch---a polyhedral subset of the surface of a convex polyhedron homeomorphic to a disk. We show that several natural…

Computational Geometry · Computer Science 2012-05-10 Joseph O'Rourke

Geometric feature learning for 3D surfaces is critical for many applications in computer graphics and 3D vision. However, deep learning currently lags in hierarchical modeling of 3D surfaces due to the lack of required operations and/or…

Computer Vision and Pattern Recognition · Computer Science 2023-04-25 Huan Lei , Naveed Akhtar , Mubarak Shah , Ajmal Mian

We present a method to match three dimensional shapes under non-isometric deformations, topology changes and partiality. We formulate the problem as matching between a set of pair-wise and point-wise descriptors, imposing a continuity prior…

Computer Vision and Pattern Recognition · Computer Science 2017-09-18 Zorah Lähner , Matthias Vestner , Amit Boyarski , Or Litany , Ron Slossberg , Tal Remez , Emanuele Rodolà , Alex Bronstein , Michael Bronstein , Ron Kimmel , Daniel Cremers

Matrix inversion problems are often encountered in experimental physics, and in particular in high-energy particle physics, under the name of unfolding. The true spectrum of a physical quantity is deformed by the presence of a detector,…

Machine Learning · Statistics 2020-09-08 Pietro Vischia

We study zero-shot 3D alignment of two given meshes, using a text prompt describing their spatial relation -- an essential capability for content creation and scene assembly. Earlier approaches primarily rely on geometric alignment…

Graphics · Computer Science 2026-03-03 Rotem Gatenyo , Ohad Fried

Designs generated by density-based topology optimization (TO) exhibit jagged and/or smeared boundaries, which forms an obstacle to their integration with existing CAD tools. Addressing this problem by smoothing or manual design adjustments…

Computational Engineering, Finance, and Science · Computer Science 2020-04-14 Marco K. Swierstra , Deepak K. Gupta , Matthijs Langelaar

In this paper, we propose the differentiable voxelization of 3D meshes via the winding number and solid angles. The proposed approach achieves fast, flexible, and accurate voxelization of 3D meshes, admitting the computation of gradients…

Computer Vision and Pattern Recognition · Computer Science 2024-07-31 Yihao Luo , Yikai Wang , Zhengrui Xiang , Yuliang Xiu , Guang Yang , ChoonHwai Yap

We propose a combinatorial solution for the problem of non-rigidly matching a 3D shape to 3D image data. To this end, we model the shape as a triangular mesh and allow each triangle of this mesh to be rigidly transformed to achieve a…

Computer Vision and Pattern Recognition · Computer Science 2017-05-19 Florian Bernard , Frank R. Schmidt , Johan Thunberg , Daniel Cremers

Image matting is generally modeled as a space transform from the color space to the alpha space. By estimating the alpha factor of the model, the foreground of an image can be extracted. However, there is some dimensional information…

Computer Vision and Pattern Recognition · Computer Science 2019-04-17 Xuelong Li , Kang Liu , Yongsheng Dong , Dacheng Tao

With the recent advances in hardware and rendering techniques, 3D models have emerged everywhere in our life. Yet creating 3D shapes is arduous and requires significant professional knowledge. Meanwhile, Deep learning has enabled…

Computer Vision and Pattern Recognition · Computer Science 2023-03-07 Zhiqin Chen

Mesh repair is a long-standing challenge in computer graphics and related fields. Converting defective meshes into watertight manifold meshes can greatly benefit downstream applications such as geometric processing, simulation, fabrication,…

Graphics · Computer Science 2023-09-04 Zhongtian Zheng , Xifeng Gao , Zherong Pan , Wei Li , Peng-Shuai Wang , Guoping Wang , Kui Wu

We present an unsupervised data-driven approach for non-rigid shape matching. Shape matching identifies correspondences between two shapes and is a fundamental step in many computer vision and graphics applications. Our approach is designed…

Computer Vision and Pattern Recognition · Computer Science 2023-11-28 Aymen Merrouche , Joao Regateiro , Stefanie Wuhrer , Edmond Boyer

Fitting an unknown number of hyperplanes to data is a fundamental yet challenging problem in machine learning, characterized by its non-convexity, non-differentiability, and unknown model order. Existing approaches often struggle with local…

Machine Learning · Computer Science 2026-05-28 Zhiqin Cheng , Yu Zhan , Mingjin Zhang , Lingbo Liu , Liang Lin

Triangle meshes remain the most popular data representation for surface geometry. This ubiquitous representation is essentially a hybrid one that decouples continuous vertex locations from the discrete topological triangulation.…

Computer Vision and Pattern Recognition · Computer Science 2021-09-23 Marie-Julie Rakotosaona , Noam Aigerman , Niloy Mitra , Maks Ovsjanikov , Paul Guerrero

This paper presents a highly efficient method to obtain high-resolution, near-optimal 3D topologies optimized for minimum compliance on a standard PC. Using an implicit geometry description we derive a single-scale interpretation of optimal…

Computational Engineering, Finance, and Science · Computer Science 2020-04-22 Jeroen Groen , Florian Stutz , Niels Aage , J. Andreas Bærentzen , Ole Sigmund

The democratization of fabrication equipment has spurred recent interest in maskless grayscale lithography for both 2D and 3D microfabrication. However, the design of suitable template images remains a challenge. This work presents a…

Some methods based on simple regularizing geometric element transformations have heuristically been shown to give runtime efficient and quality effective smoothing algorithms for meshes. We describe the mathematical framework and a…

Computational Geometry · Computer Science 2013-07-09 Dimitris Vartziotis , Benjamin Himpel