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Related papers: QuadGPT: Native Quadrilateral Mesh Generation with…

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The generation of production-ready quad-dominant meshes is a cornerstone of modern 3D content creation. Generating anisotropic quad-dominant meshes from point clouds is challenging, as existing methods are typically limited to producing…

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

High-quality quadrilateral mesh generation is a fundamental challenge in computer graphics. Traditional optimization-based methods are often constrained by the topological quality of input meshes and suffer from severe efficiency…

Graphics · Computer Science 2026-03-12 Yuguang Chen , Xinhai Liu , Xiangyu Zhu , Yiling Zhu , Zhuo Chen , Dongyu Zhang , Chunchao Guo

We introduce TreeMeshGPT, an autoregressive Transformer designed to generate high-quality artistic meshes aligned with input point clouds. Instead of the conventional next-token prediction in autoregressive Transformer, we propose a novel…

Graphics · Computer Science 2025-03-17 Stefan Lionar , Jiabin Liang , Gim Hee Lee

Autoregressive transformers have revolutionized generative models in language processing and shown substantial promise in image and video generation. However, these models face significant challenges when extended to 3D generation tasks due…

Computer Vision and Pattern Recognition · Computer Science 2024-09-11 Jinzhi Zhang , Feng Xiong , Mu Xu

Most recent advances in 3D generative modeling rely on diffusion or flow-matching formulations. We instead explore a fully autoregressive alternative and introduce GaussianGPT, a transformer-based model that directly generates 3D Gaussians…

Computer Vision and Pattern Recognition · Computer Science 2026-03-30 Nicolas von Lützow , Barbara Rössle , Katharina Schmid , Matthias Nießner

Meshes serve as a primary representation for 3D assets. Autoregressive mesh generators serialize faces into sequences and train on truncated segments with sliding-window inference to cope with memory limits. However, this mismatch breaks…

Computer Vision and Pattern Recognition · Computer Science 2025-12-10 Junkai Lin , Hang Long , Huipeng Guo , Jielei Zhang , JiaYi Yang , Tianle Guo , Yang Yang , Jianwen Li , Wenxiao Zhang , Matthias Nießner , Wei Yang

Existing auto-regressive mesh generation approaches suffer from ineffective topology preservation, which is crucial for practical applications. This limitation stems from previous mesh tokenization methods treating meshes as simple…

Computer Vision and Pattern Recognition · Computer Science 2026-03-03 Gaochao Song , Zibo Zhao , Haohan Weng , Jingbo Zeng , Rongfei Jia , Shenghua Gao

Autoregressive models have achieved remarkable success across various domains, yet their performance in 3D shape generation lags significantly behind that of diffusion models. In this paper, we introduce OctGPT, a novel multiscale…

Graphics · Computer Science 2025-04-16 Si-Tong Wei , Rui-Huan Wang , Chuan-Zhi Zhou , Baoquan Chen , Peng-Shuai Wang

Quad meshes are essential in geometric modeling and computational mechanics. Although learning-based methods for triangle mesh demonstrate considerable advancements, quad mesh generation remains less explored due to the challenge of…

Computer Vision and Pattern Recognition · Computer Science 2025-04-29 Zezeng Li , Zhihui Qi , Weimin Wang , Ziliang Wang , Junyi Duan , Na Lei

We propose an end-to-end pipeline to robustly generate high-quality quadrilateral meshes for complex CAD models. An initial quad-dominant mesh is generated with frontal point insertion guided by a locally integrable cross field and a scalar…

Computational Engineering, Finance, and Science · Computer Science 2021-03-09 Maxence Reberol , Christos Georgiadis , Jean-François Remacle

We introduce AutoPartGen, a model that generates objects composed of 3D parts in an autoregressive manner. This model can take as input an image of an object, 2D masks of the object's parts, or an existing 3D object, and generate a…

Computer Vision and Pattern Recognition · Computer Science 2025-07-22 Minghao Chen , Jianyuan Wang , Roman Shapovalov , Tom Monnier , Hyunyoung Jung , Dilin Wang , Rakesh Ranjan , Iro Laina , Andrea Vedaldi

Numerous methods have been proposed for probabilistic generative modelling of 3D objects. However, none of these is able to produce textured objects, which renders them of limited use for practical tasks. In this work, we present the first…

Computer Vision and Pattern Recognition · Computer Science 2020-04-10 Paul Henderson , Vagia Tsiminaki , Christoph H. Lampert

Triangle meshes play a crucial role in 3D applications for efficient manipulation and rendering. While auto-regressive methods generate structured meshes by predicting discrete vertex tokens, they are often constrained by limited face…

Computer Vision and Pattern Recognition · Computer Science 2025-03-20 Ruowen Zhao , Junliang Ye , Zhengyi Wang , Guangce Liu , Yiwen Chen , Yikai Wang , Jun Zhu

We present SketchGPT, a flexible framework that employs a sequence-to-sequence autoregressive model for sketch generation, and completion, and an interpretation case study for sketch recognition. By mapping complex sketches into simplified…

Computer Vision and Pattern Recognition · Computer Science 2024-05-07 Adarsh Tiwari , Sanket Biswas , Josep Lladós

Surface cutting is a fundamental task in computer graphics, with applications in UV parameterization, texture mapping, and mesh decomposition. However, existing methods often produce technically valid but overly fragmented atlases that lack…

Recent mesh generation approaches typically tokenize triangle meshes into sequences of tokens and train autoregressive models to generate these tokens sequentially. Despite substantial progress, such token sequences inevitably reuse…

Computer Vision and Pattern Recognition · Computer Science 2026-01-16 Jeonghwan Kim , Yushi Lan , Armando Fortes , Yongwei Chen , Xingang Pan

3D meshes are a critical building block for applications ranging from industrial design and gaming to simulation and robotics. Traditionally, meshes are crafted manually by artists, a process that is time-intensive and difficult to scale.…

Computer Vision and Pattern Recognition · Computer Science 2025-11-24 Xiatao Sun , Chen Liang , Qian Wang , Daniel Rakita

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

Directly generating 3D meshes, the default representation for 3D shapes in the graphics industry, using auto-regressive (AR) models has become popular these days, thanks to their sharpness, compactness in the generated results, and ability…

Graphics · Computer Science 2025-09-26 Jiabao Lei , Kewei Shi , Zhihao Liang , Kui Jia
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