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When obtaining interior 3D voxel data from triangular meshes, most existing methods fail to handle low quality meshes which happens to take up a big portion on the internet. In this work we present a robust voxelization method that is based…

Graphics · Computer Science 2021-07-22 Joseph Chen , Ko-Wei Tai , Wen-Chin Chen , Ming Ouhyoung

We present a method for generating high-quality watertight manifold meshes from multi-view input images. Existing volumetric rendering methods are robust in optimization but tend to generate noisy meshes with poor topology. Differentiable…

Computer Vision and Pattern Recognition · Computer Science 2025-01-20 Xinyue Wei , Fanbo Xiang , Sai Bi , Anpei Chen , Kalyan Sunkavalli , Zexiang Xu , Hao Su

Recent work in Neural Fields (NFs) learn 3D representations from class-specific single view image collections. However, they are unable to reconstruct the input data preserving high-frequency details. Further, these methods do not…

Computer Vision and Pattern Recognition · Computer Science 2023-03-27 Vishal Vinod , Tanmay Shah , Dmitry Lagun

The crystallographic texture is a key organization feature of many technical and biological materials. In these materials, especially hierarchically structured ones, the preferential alignment of the nano constituents is heavily influencing…

The generation of triangle meshes from point clouds, i.e. meshing, is a core task in computer graphics and computer vision. Traditional techniques directly construct a surface mesh using local decision heuristics, while some recent methods…

Computer Vision and Pattern Recognition · Computer Science 2022-10-06 Mathias Vetsch , Sandro Lombardi , Marc Pollefeys , Martin R. Oswald

Generative reconstruction methods compute the 3D configuration (such as pose and/or geometry) of a shape by optimizing the overlap of the projected 3D shape model with images. Proper handling of occlusions is a big challenge, since the…

Computer Vision and Pattern Recognition · Computer Science 2016-02-12 Helge Rhodin , Nadia Robertini , Christian Richardt , Hans-Peter Seidel , Christian Theobalt

Generating 3D content from a single image remains a fundamentally challenging and ill-posed problem due to the inherent absence of geometric and textural information in occluded regions. While state-of-the-art generative models can…

Computer Vision and Pattern Recognition · Computer Science 2026-02-12 Zehua Ma , Hanhui Li , Zhenyu Xie , Xiaonan Luo , Michael Kampffmeyer , Feng Gao , Xiaodan Liang

Texture mapping is a common technology in the area of computer graphics, it maps the 3D surface space onto the 2D texture space. However, the loose texture space will reduce the efficiency of data storage and GPU memory addressing in the…

Computer Vision and Pattern Recognition · Computer Science 2025-03-26 Wei Chen , Yuxue Ren , Na Lei , Zhongxuan Luo , Xianfeng Gu

Mesh seams play a pivotal role in partitioning 3D surfaces for UV parametrization and texture mapping. Poorly placed seams often result in severe UV distortion or excessive fragmentation, thereby hindering texture synthesis and disrupting…

Graphics · Computer Science 2025-09-29 Duoteng Xu , Yuguang Chen , Jing Li , Xinhai Liu , Xueqi Ma , Zhuo Chen , Dongyu Zhang , Chunchao Guo

We present a new effective way for performance capture of deforming meshes with fine-scale time-varying surface detail from multi-view video. Our method builds up on coarse 4D surface reconstructions, as obtained with commonly used…

Computer Vision and Pattern Recognition · Computer Science 2016-02-08 Nadia Robertini , Edilson De Aguiar , Thomas Helten , Christian Theobalt

High-order quadrilateral meshes offer superior accuracy and computational efficiency in numerical simulations. However, existing methods struggle to simultaneously preserve boundary/interface features, ensure high quality, and achieve…

Graphics · Computer Science 2026-03-25 Yongjia Weng , Lufeng Liu , Zhonggui Chen , Xuan Zhou , Juan Cao

We propose a novel approach to reconstruct RGB-D indoor scene based on plane primitives. Our approach takes as input a RGB-D sequence and a dense coarse mesh reconstructed from it, and generates a lightweight, low-polygonal mesh with clear…

Computer Vision and Pattern Recognition · Computer Science 2019-05-23 Chao Wang , Xiaohu Guo

We present a novel approach to detect, segment, and reconstruct complete textured 3D models of vehicles from a single image for autonomous driving. Our approach combines the strengths of deep learning and the elegance of traditional…

Computer Vision and Pattern Recognition · Computer Science 2020-07-17 Feixiang Lu , Zongdai Liu , Xibin Song , Dingfu Zhou , Wei Li , Hui Miao , Miao Liao , Liangjun Zhang , Bin Zhou , Ruigang Yang , Dinesh Manocha

We present an efficient method for joint optimization of topology, materials and lighting from multi-view image observations. Unlike recent multi-view reconstruction approaches, which typically produce entangled 3D representations encoded…

Computer Vision and Pattern Recognition · Computer Science 2023-04-12 Jacob Munkberg , Jon Hasselgren , Tianchang Shen , Jun Gao , Wenzheng Chen , Alex Evans , Thomas Müller , Sanja Fidler

Learning to generate textures for a novel 3D mesh given a collection of 3D meshes and real-world 2D images is an important problem with applications in various domains such as 3D simulation, augmented and virtual reality, gaming,…

Computer Vision and Pattern Recognition · Computer Science 2024-03-08 Dharma KC , Clayton T. Morrison

Texture cues on 3D objects are key to compelling visual representations, with the possibility to create high visual fidelity with inherent spatial consistency across different views. Since the availability of textured 3D shapes remains very…

Computer Vision and Pattern Recognition · Computer Science 2022-04-07 Yawar Siddiqui , Justus Thies , Fangchang Ma , Qi Shan , Matthias Nießner , Angela Dai

3D content generation has wide applications in various fields. One of its dominant paradigms is by sparse-view reconstruction using multi-view images generated by diffusion models. However, since directly reconstructing triangle meshes from…

Computer Vision and Pattern Recognition · Computer Science 2024-05-28 Ruowen Zhao , Zhengyi Wang , Yikai Wang , Zihan Zhou , Jun Zhu

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

We present a novel framework for mesh reconstruction from unstructured point clouds by taking advantage of the learned visibility of the 3D points in the virtual views and traditional graph-cut based mesh generation. Specifically, we first…

Computer Vision and Pattern Recognition · Computer Science 2021-08-20 Shuang Song , Zhaopeng Cui , Rongjun Qin

4D head capture aims to generate dynamic topological meshes and corresponding texture maps from videos, which is widely utilized in movies and games for its ability to simulate facial muscle movements and recover dynamic textures in…

Computer Vision and Pattern Recognition · Computer Science 2024-07-16 Xuanchen Li , Yuhao Cheng , Xingyu Ren , Haozhe Jia , Di Xu , Wenhan Zhu , Yichao Yan
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