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Related papers: DMesh: A Differentiable Mesh Representation

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Researchers have now achieved great success on dealing with 2D images using deep learning. In recent years, 3D computer vision and Geometry Deep Learning gain more and more attention. Many advanced techniques for 3D shapes have been…

Graphics · Computer Science 2020-04-16 Yun-Peng Xiao , Yu-Kun Lai , Fang-Lue Zhang , Chunpeng Li , Lin Gao

We propose a two-stage algorithm for generating Delaunay triangulations in 2D and Delaunay tetrahedra in 3D that employs near maximal Poisson-disk sampling. The method generates a variable resolution mesh in 2- and 3-dimensions in linear…

Numerical Analysis · Mathematics 2021-05-24 Johannes Krotz , Matthew R. Sweeney , Carl W. Gable , Jeffrey D. Hyman , Juan M. Restrepo

This paper addresses the challenges of designing mesh convolution neural networks for 3D mesh dense prediction. While deep learning has achieved remarkable success in image dense prediction tasks, directly applying or extending these…

Computer Vision and Pattern Recognition · Computer Science 2024-08-27 Shi Hezi , Jiang Luo , Zheng Jianmin , Zeng Jun

In this work, we focus on the task of learning and representing dense correspondences in deformable object categories. While this problem has been considered before, solutions so far have been rather ad-hoc for specific object types (i.e.,…

Computer Vision and Pattern Recognition · Computer Science 2020-11-26 Natalia Neverova , David Novotny , Vasil Khalidov , Marc Szafraniec , Patrick Labatut , Andrea Vedaldi

Polygon meshes are an efficient representation of 3D geometry, and are of central importance in computer graphics, robotics and games development. Existing learning-based approaches have avoided the challenges of working with 3D meshes,…

Graphics · Computer Science 2020-02-26 Charlie Nash , Yaroslav Ganin , S. M. Ali Eslami , Peter W. Battaglia

As the most common representation for 3D shapes, mesh is often stored discretely with arrays of vertices and faces. However, 3D shapes in the real world are presented continuously. In this paper, we propose to learn a continuous…

Computer Vision and Pattern Recognition · Computer Science 2023-01-13 Zhongpai Gao

In this paper, we present a novel strategy to design disentangled 3D face shape representation. Specifically, a given 3D face shape is decomposed into identity part and expression part, which are both encoded and decoded in a nonlinear way.…

Computer Vision and Pattern Recognition · Computer Science 2019-03-05 Zi-Hang Jiang , Qianyi Wu , Keyu Chen , Juyong Zhang

Differentiable render is widely used in optimization-based 3D reconstruction which requires gradients from differentiable operations for gradient-based optimization. The existing differentiable renderers obtain the gradients of rendering…

Computer Vision and Pattern Recognition · Computer Science 2019-06-20 Zaiqiang Wu , Wei Jiang

Learning radiance fields (NeRF) with powerful 2D diffusion models has garnered popularity for text-to-3D generation. Nevertheless, the implicit 3D representations of NeRF lack explicit modeling of meshes and textures over surfaces, and such…

Computer Vision and Pattern Recognition · Computer Science 2024-09-12 Haibo Yang , Yang Chen , Yingwei Pan , Ting Yao , Zhineng Chen , Zuxuan Wu , Yu-Gang Jiang , Tao Mei

Textured meshes significantly enhance the realism and detail of objects by mapping intricate texture details onto the geometric structure of 3D models. This advancement is valuable across various applications, including entertainment,…

Graphics · Computer Science 2024-12-12 Kaiwei Zhang , Dandan Zhu , Xiongkuo Min , Guangtao Zhai

Information transfer between triangle meshes is of great importance in computer graphics and geometry processing. To facilitate this process, a smooth and accurate map is typically required between the two meshes. While such maps can…

Graphics · Computer Science 2018-01-09 Danielle Ezuz , Justin Solomon , Mirela Ben-Chen

Differentiable rendering is an essential operation in modern vision, allowing inverse graphics approaches to 3D understanding to be utilized in modern machine learning frameworks. Explicit shape representations (voxels, point clouds, or…

Computer Vision and Pattern Recognition · Computer Science 2021-12-13 Tristan Aumentado-Armstrong , Stavros Tsogkas , Sven Dickinson , Allan Jepson

3D geometric contents are becoming increasingly popular. In this paper, we study the problem of analyzing deforming 3D meshes using deep neural networks. Deforming 3D meshes are flexible to represent 3D animation sequences as well as…

Graphics · Computer Science 2018-03-30 Qingyang Tan , Lin Gao , Yu-Kun Lai , Shihong Xia

Deep generative models have shown success in generating 3D shapes with different representations. In this work, we propose Neural Volumetric Mesh Generator(NVMG) which can generate novel and high-quality volumetric meshes. Unlike the…

Computer Vision and Pattern Recognition · Computer Science 2022-10-10 Yan Zheng , Lemeng Wu , Xingchao Liu , Zhen Chen , Qiang Liu , Qixing Huang

Generative models that produce point clouds have emerged as a powerful tool to represent 3D surfaces, and the best current ones rely on learning an ensemble of parametric representations. Unfortunately, they offer no control over the…

Computer Vision and Pattern Recognition · Computer Science 2019-11-27 Jan Bednarik , Shaifali Parashar , Erhan Gundogdu , Mathieu Salzmann , Pascal Fua

A completely well-centered tetrahedral mesh is a triangulation of a three dimensional domain in which every tetrahedron and every triangle contains its circumcenter in its interior. Such meshes have applications in scientific computing and…

Computational Geometry · Computer Science 2008-08-06 Evan VanderZee , Anil N. Hirani , Damrong Guoy

Generating high-quality meshes with complex structures and realistic surfaces is the primary goal of 3D generative models. Existing methods typically employ sequence data or deformable tetrahedral grids for mesh generation. However,…

Computer Vision and Pattern Recognition · Computer Science 2024-10-24 Ruowei Wang , Jiaqi Li , Dan Zeng , Xueqi Ma , Zixiang Xu , Jianwei Zhang , Qijun Zhao

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

Triangular meshes are a widely used representation in the field of 3D modeling. In this paper, we present a novel approach for edge length-based linear subdivision on triangular meshes, along with two auxiliary techniques. We conduct a…

Graphics · Computer Science 2023-10-04 Junyi Shen

The creation of photorealistic virtual worlds requires the accurate modeling of 3D surface geometry for a wide range of objects. For this, meshes are appealing since they 1) enable fast physics-based rendering with realistic material and…

Computer Vision and Pattern Recognition · Computer Science 2024-03-26 Zhen Liu , Yao Feng , Yuliang Xiu , Weiyang Liu , Liam Paull , Michael J. Black , Bernhard Schölkopf