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Related papers: SeqTex: Generate Mesh Textures in Video Sequence

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This paper presents Paint3D, a novel coarse-to-fine generative framework that is capable of producing high-resolution, lighting-less, and diverse 2K UV texture maps for untextured 3D meshes conditioned on text or image inputs. The key…

Computer Vision and Pattern Recognition · Computer Science 2023-12-25 Xianfang Zeng , Xin Chen , Zhongqi Qi , Wen Liu , Zibo Zhao , Zhibin Wang , Bin Fu , Yong Liu , Gang Yu

3D vector graphics play a crucial role in various applications including 3D shape retrieval, conceptual design, and virtual reality interactions due to their ability to capture essential structural information with minimal representation.…

Computer Vision and Pattern Recognition · Computer Science 2025-05-27 Chuang Wang , Haitao Zhou , Ling Luo , Qian Yu

Reconstructing 3D human faces in the wild with the 3D Morphable Model (3DMM) has become popular in recent years. While most prior work focuses on estimating more robust and accurate geometry, relatively little attention has been paid to…

Graphics · Computer Science 2020-11-26 Myunggi Lee , Wonwoong Cho , Moonheum Kim , David Inouye , Nojun Kwak

Texture map production is an important part of 3D modeling and determines the rendering quality. Recently, diffusion-based methods have opened a new way for texture generation. However, restricted control flexibility and limited prompt…

Graphics · Computer Science 2025-06-04 Dongyu Yan , Leyi Wu , Jiantao Lin , Luozhou Wang , Tianshuo Xu , Zhifei Chen , Zhen Yang , Lie Xu , Shunsi Zhang , Yingcong Chen

While recent generative models for 2D images achieve impressive visual results, they clearly lack the ability to perform 3D reasoning. This heavily restricts the degree of control over generated objects as well as the possible applications…

Computer Vision and Pattern Recognition · Computer Science 2020-10-26 Dario Pavllo , Graham Spinks , Thomas Hofmann , Marie-Francine Moens , Aurelien Lucchi

This report presents a comprehensive framework for generating high-quality 3D shapes and textures from diverse input prompts, including single images, multi-view images, and text descriptions. The framework consists of 3D shape generation…

There has been a recent surge in methods that aim to decompose and segment scenes into multiple objects in an unsupervised manner, i.e., unsupervised multi-object segmentation. Performing such a task is a long-standing goal of computer…

Computer Vision and Pattern Recognition · Computer Science 2021-11-22 Laurynas Karazija , Iro Laina , Christian Rupprecht

We present GenesisTex, a novel method for synthesizing textures for 3D geometries from text descriptions. GenesisTex adapts the pretrained image diffusion model to texture space by texture space sampling. Specifically, we maintain a latent…

Computer Vision and Pattern Recognition · Computer Science 2024-03-27 Chenjian Gao , Boyan Jiang , Xinghui Li , Yingpeng Zhang , Qian Yu

We are witnessing a proliferation of textured 3D models captured from the real world with automatic photo-reconstruction tools. Digital 3D models of this class come with a unique set of characteristics and defects -- especially concerning…

Graphics · Computer Science 2020-12-29 Andrea Maggiordomo , Federico Ponchio , Paolo Cignoni , Marco Tarini

This study aims to investigate the challenge of insufficient three-dimensional context in synthetic datasets for scene text rendering. Although recent advances in diffusion models and related techniques have improved certain aspects of…

Computer Vision and Pattern Recognition · Computer Science 2025-05-27 Li-Syun Hsiung , Jun-Kai Tu , Kuan-Wu Chu , Yu-Hsuan Chiu , Yan-Tsung Peng , Sheng-Luen Chung , Gee-Sern Jison Hsu

Although recent advances have improved the quality of 3D texture generation, existing methods still struggle with incomplete texture coverage, cross-view inconsistency, and misalignment between geometry and texture. To address these…

Computer Vision and Pattern Recognition · Computer Science 2026-04-13 Huiang He , Shengchu Zhao , Jianwen Huang , Jie Li , Jiaqi Wu , Hu Zhang , Pei Tang , Heliang Zheng , Yukun Li , Rongfei Jia

The creation of high-fidelity, customizable 3D indoor scene textures remains a significant challenge. While text-driven methods offer flexibility, they lack the precision for fine-grained, instance-level control, and often produce textures…

Computer Vision and Pattern Recognition · Computer Science 2026-03-23 Weilin Chen , Jiahao Rao , Wenhao Wang , Xinyang Li , Xuan Cheng , Liujuan Cao

Despite the availability of large-scale 3D datasets and advancements in 3D generative models, the complexity and uneven quality of 3D geometry and texture data continue to hinder the performance of 3D generation techniques. In most existing…

Computer Vision and Pattern Recognition · Computer Science 2025-05-29 Xin Yang , Jiantao Lin , Yingjie Xu , Haodong Li , Yingcong Chen

We present GOATex, a diffusion-based method for 3D mesh texturing that generates high-quality textures for both exterior and interior surfaces. While existing methods perform well on visible regions, they inherently lack mechanisms to…

Computer Vision and Pattern Recognition · Computer Science 2025-12-01 Hyunjin Kim , Kunho Kim , Adam Lee , Wonkwang Lee

We present PacTure, a novel framework for generating physically-based rendering (PBR) material textures for an untextured 3D mesh from a text description. Existing 2D generation-based texturing approaches either generate textures…

Computer Vision and Pattern Recognition · Computer Science 2026-05-15 Fan Fei , Jiajun Tang , Fei-Peng Tian , Boxin Shi , Ping Tan

Recent progress in image and video synthesis has inspired their use in advancing 3D scene generation. However, we observe that text-to-image and -video approaches struggle to maintain scene- and object-level consistency beyond a limited…

Computer Vision and Pattern Recognition · Computer Science 2026-03-26 Manuel-Andreas Schneider , Angela Dai

Fabricating and designing 3D garments has become extremely demanding with the increasing need for synthesizing realistic dressed persons for a variety of applications, e.g. 3D virtual try-on, digitalization of 2D clothes into 3D apparel,…

Computer Vision and Pattern Recognition · Computer Science 2023-08-09 Daiheng Gao , Xu Chen , Xindi Zhang , Qi Wang , Ke Sun , Bang Zhang , Liefeng Bo , Qixing Huang

Recent 3D generative models produce high-quality textures for 3D mesh objects. However, they commonly rely on the heavy assumption that input 3D meshes are accompanied by manual mesh parameterization (UV mapping), a manual task that…

Graphics · Computer Science 2026-03-02 AmirHossein Zamani , Bruno Roy , Arianna Rampini

Automatically generating photorealistic and self-consistent appearances for untextured 3D models is a critical challenge in digital content creation. The advancement of large-scale video generation models offers a natural approach: directly…

Computer Vision and Pattern Recognition · Computer Science 2026-03-19 Yan Zeng , Haoran Jiang , Kaixin Yao , Qixuan Zhang , Longwen Zhang , Lan Xu , Jingyi Yu

We introduce VERTEX, an effective solution to recover 3D shape and intrinsic texture of vehicles from uncalibrated monocular input in real-world street environments. To fully utilize the template prior of vehicles, we propose a novel…

Computer Vision and Pattern Recognition · Computer Science 2021-03-30 Xiaochen Zhao , Zerong Zheng , Chaonan Ji , Zhenyi Liu , Siyou Lin , Tao Yu , Jinli Suo , Yebin Liu