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Despite the promising results of multi-view reconstruction, the recent neural rendering-based methods, such as implicit surface rendering (IDR) and volume rendering (NeuS), not only incur a heavy computational burden on training but also…

Computer Vision and Pattern Recognition · Computer Science 2023-05-30 Yisu Zhang , Jianke Zhu , Lixiang Lin

We present InstantMesh, a feed-forward framework for instant 3D mesh generation from a single image, featuring state-of-the-art generation quality and significant training scalability. By synergizing the strengths of an off-the-shelf…

Computer Vision and Pattern Recognition · Computer Science 2024-04-16 Jiale Xu , Weihao Cheng , Yiming Gao , Xintao Wang , Shenghua Gao , Ying Shan

We present an end-to-end framework for generating artist-style meshes from noisy or incomplete point clouds, such as those captured by real-world sensors like LiDAR or mobile RGB-D cameras. Artist-created meshes are crucial for commercial…

Computer Vision and Pattern Recognition · Computer Science 2025-09-17 Yao He , Youngjoong Kwon , Wenxiao Cai , Ehsan Adeli

Mesh generation is a crucial step in numerical simulations, significantly impacting simulation accuracy and efficiency. However, generating meshes remains time-consuming and requires expensive computational resources. In this paper, we…

Graphics · Computer Science 2024-07-03 Jiaming Peng , Xinhai Chen , Jie Liu

We consider the task of generating realistic 3D shapes, which is useful for a variety of applications such as automatic scene generation and physical simulation. Compared to other 3D representations like voxels and point clouds, meshes are…

Graphics · Computer Science 2023-04-18 Zhen Liu , Yao Feng , Michael J. Black , Derek Nowrouzezahrai , Liam Paull , Weiyang Liu

Handling the ever-increasing complexity of mesh generation codes along with the intricacies of newer hardware often results in codes that are both difficult to comprehend and maintain. Different facets of codes such as thread management and…

Distributed, Parallel, and Cluster Computing · Computer Science 2024-04-30 Christos Tsolakis , Polykarpos Thomadakis , Nikos Chrisochoides

Articulated 3D object generation is fundamental for creating realistic, functional, and interactable virtual assets which are not simply static. We introduce MeshArt, a hierarchical transformer-based approach to generate articulated 3D…

Computer Vision and Pattern Recognition · Computer Science 2025-06-10 Daoyi Gao , Yawar Siddiqui , Lei Li , Angela Dai

We introduce MeshGPT, a new approach for generating triangle meshes that reflects the compactness typical of artist-created meshes, in contrast to dense triangle meshes extracted by iso-surfacing methods from neural fields. Inspired by…

Computer Vision and Pattern Recognition · Computer Science 2023-11-28 Yawar Siddiqui , Antonio Alliegro , Alexey Artemov , Tatiana Tommasi , Daniele Sirigatti , Vladislav Rosov , Angela Dai , Matthias Nießner

We propose a compressive yet effective mesh representation, Blocked and Patchified Tokenization (BPT), facilitating the generation of meshes exceeding 8k faces. BPT compresses mesh sequences by employing block-wise indexing and patch…

Mesh generation plays a crucial role in scientific computing. Traditional mesh generation methods, such as TFI and PDE-based methods, often struggle to achieve a balance between efficiency and mesh quality. To address this challenge,…

Machine Learning · Computer Science 2025-01-23 Jing Xiao , Xinhai Chen , Qingling Wang , Jie Liu

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

High-fidelity 3D meshes can be tokenized into one-dimension (1D) sequences and directly modeled using autoregressive approaches for faces and vertices. However, existing methods suffer from insufficient resource utilization, resulting in…

Computer Vision and Pattern Recognition · Computer Science 2026-01-30 Yanfeng Li , Tao Tan , Qingquan Gao , Zhiwen Cao , Xiaohong liu , Yue Sun

Current auto-regressive mesh generation methods suffer from issues such as incompleteness, insufficient detail, and poor generalization. In this paper, we propose an Auto-regressive Auto-encoder (ArAE) model capable of generating…

Computer Vision and Pattern Recognition · Computer Science 2024-09-27 Jiaxiang Tang , Zhaoshuo Li , Zekun Hao , Xian Liu , Gang Zeng , Ming-Yu Liu , Qinsheng Zhang

Meshes are ubiquitous in visual computing and simulation, yet most existing machine learning techniques represent meshes only indirectly, e.g. as the level set of a scalar field or deformation of a template, or as a disordered triangle soup…

Computer Vision and Pattern Recognition · Computer Science 2025-02-12 Tianchang Shen , Zhaoshuo Li , Marc Law , Matan Atzmon , Sanja Fidler , James Lucas , Jun Gao , Nicholas Sharp

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

We introduce a novel approach to automatic unstructured mesh generation using machine learning to predict an optimal finite element mesh for a previously unseen problem. The framework that we have developed is based around training an…

Numerical Analysis · Mathematics 2020-04-16 Zheyan Zhang , Yongxing Wang , Peter K. Jimack , He Wang

Mesh generation remains a key technology in many areas where numerical simulations are required. As numerical algorithms become more efficient and computers become more powerful, the percentage of time devoted to mesh generation becomes…

Graphics · Computer Science 2022-10-19 Xinhai Chen , Jie Liu , Junjun Yan , Zhichao Wang , Chunye Gong

Recent advances in 3D vision have led to specialized models for either 3D understanding (e.g., shape classification, segmentation, reconstruction) or 3D generation (e.g., synthesis, completion, and editing). However, these tasks are often…

Computer Vision and Pattern Recognition · Computer Science 2026-04-21 Peng Huang , Yifeng Chen , Zeyu Zhang , Hao Tang

Recent deep image-to-image translation techniques allow fast generation of face images from freehand sketches. However, existing solutions tend to overfit to sketches, thus requiring professional sketches or even edge maps as input. To…

Graphics · Computer Science 2020-06-09 Shu-Yu Chen , Wanchao Su , Lin Gao , Shihong Xia , Hongbo Fu

In this paper, we introduce MeshGen, an advanced image-to-3D pipeline that generates high-quality 3D meshes with detailed geometry and physically based rendering (PBR) textures. Addressing the challenges faced by existing 3D native…

Graphics · Computer Science 2025-05-09 Zilong Chen , Yikai Wang , Wenqiang Sun , Feng Wang , Yiwen Chen , Huaping Liu