MVPaint: Synchronized Multi-View Diffusion for Painting Anything 3D
Wei Cheng, Juncheng Mu, Xianfang Zeng, Xin Chen, Anqi Pang, Chi Zhang, Zhibin Wang, Bin Fu, Gang Yu, Ziwei Liu, Liang Pan
Abstract
Abstract Texturing is a crucial step in the 3D asset production workflow, which enhances the visual appeal and diversity of 3D assets. Despite recent advancements in Text-to-Texture (T2T) generation, existing methods often yield subpar results, primarily due to local discontinuities, inconsistencies across multiple views, and heavy dependence on UV unwrapping outcomes. To tackle these challenges, we propose a novel generation-refinement 3D texturing framework called MVPaint, which can generate high-resolution, seamless textures while emphasizing multi-view consistency. MVPaint mainly consists of three key modules. 1) Synchronized Multi-view Generation (SMG). Given a 3D mesh model, MVPaint first simultaneously generates multiview images by employing a SMG model, which leads to coarse texturing results with unpainted parts due to missing observations. 2) Spatial-aware 3D Inpainting (S3I). To ensure complete 3D texturing, we introduce the S3I method, specifically designed to texture previously unobserved areas effectively. 3) UV Refinement (UVR). Furthermore, MVPaint employs a UVR module to improve the texture quality in the UV space, which first performs a UVspace Super-Resolution, followed by a Spatial-aware Seam-Smoothing algorithm for revising spatial texturing discontinuities caused by UV unwrapping. Moreover, we establish two T2T evaluation benchmarks: the Objaverse T2T benchmark and the GSO T2T benchmark, based on selected high-quality 3D meshes from the Objaverse dataset and the entire GSO dataset, respectively. Extensive experimental results demonstrate that MVPaint surpasses existing stateof-the-art methods. Notably, MVPaint could generate highfidelity textures with minimal Janus issues and highly enhanced cross-view consistency.
Ask about this paper
Your agent reads all of it.
Lune indexed this paper to the last equation, along with the top-tier papers that cite it. Ask a question and the answer quotes them.
Your agent calls
Luneget_paper_fulltext
Free to start. No credit card required.
Terminal
Install the CLIlune papers fulltext 4f53f915-ff0a-4b15-a41e-6c3defc218b3Cited by top-tier papers6
- Unlearning Concepts in Diffusion Model via Concept Domain Correction and Concept Preserving GradientYongliang Wu, Shiji Zhou, Mingzhuo Yang, Lianzhe Wang et al.AAAI 2025 · 69 citations
- Lafite: A Generative Latent Field for 3D Native TexturingChia-Hao Chen, Yuan-Chen Guo, Zi-Xin Zou, Ze Yuan et al.CVPR 2026 · 6 citations
- GaussianGrow: Geometry-aware Gaussian Growing from 3D Point Clouds with Text GuidanceWeiqi Zhang, Junsheng Zhou, Haotian Geng, Kanle Shi et al.CVPR 2026 · 2 citations
- GAP: Gaussianize Any Point Clouds with Text GuidanceWeiqi Zhang, Junsheng Zhou, Haotian Geng, Wenyuan Zhang et al.ICCV 2025 · 2 citations
- VecSet-Edit: Unleashing Pre-trained LRM for Mesh Editing from Single ImageTeng-Fang Hsiao, Bo-Kai Ruan, Yu-Lun Liu, Hong-Han ShuaiSIGGRAPH 2026 · 1 citation
Builds on29
- Learning Transferable Visual Models From Natural Language SupervisionAlec Radford, Jong Wook Kim, Chris Hallacy, Aditya Ramesh et al.ICML 2021 · 47,906 citations
- Denoising Diffusion Probabilistic ModelsJonathan Ho, Ajay Jain, Pieter AbbeelNeurIPS 2020 · 35,902 citations
- High-Resolution Image Synthesis with Latent Diffusion ModelsRobin Rombach, Andreas Blattmann, Dominik Lorenz, Patrick Esser et al.CVPR 2022 · 13,123 citations
- Denoising Diffusion Implicit ModelsJiaming Song, Chenlin Meng, Stefano ErmonICLR 2021 · 11,743 citations
- Adding Conditional Control to Text-to-Image Diffusion ModelsLvmin Zhang, Anyi Rao, Maneesh AgrawalaICCV 2023 · 6,759 citations
Related papers
- MV2UV: Generating High-quality UV Texture Maps with Multiview PromptsZheng Zhang, Qinchuan Zhang, Yuteng Ye, Zhi Chen et al.CVPR 2026
- RomanTex: Decoupling 3D-Aware Rotary Positional Embedded Multi-Attention Network for Texture SynthesisYifei Feng, Mingxin Yang, Shuhui Yang, Sheng Zhang et al.ICCV 2025 · 3 citations
- AlignTex: Pixel-Precise Texture Generation from Multi-view ArtworkYuqing Zhang, Hao Xu, Yiqian Wu, Sirui Chen et al.SIGGRAPH 2025 · 4 citations
- Paint3D: Paint Anything 3D With Lighting-Less Texture Diffusion ModelsXianfang Zeng, Xin Chen, Zhongqi Qi, Wen Liu et al.CVPR 2024 · 44 citations
- UniTEX: Universal High Fidelity Generative Texturing for 3D ShapesYixun Liang, Kunming Luo, Xiao Chen, Rui Chen et al.CVPR 2026 · 27 citations
