FlexPainter: Flexible and Multi-View Consistent Texture Generation
On the map: Diffusion models → 3D, point cloud and scene generation
Abstract (arXiv)
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 modalities may prevent creators from producing desired results. Furthermore, inconsistencies between generated multi-view images often lead to poor texture generation quality. To address these issues, we introduce FlexPainter, a novel texture generation pipeline that enables flexible multi-modal conditional guidance and achieves highly consistent texture generation. A shared conditional embedding space is constructed to perform flexible aggregation between different input modalities. Utilizing such embedding space, we present an image-based CFG method to decompose structural and style information, achieving reference image-based stylization. Leveraging the 3D knowledge within the image diffusion prior, we first generate multi-view images simultaneously using a grid representation to enhance global understanding. Meanwhile, we propose a view synchronization and adaptive weighting module during diffusion sampling to further ensure local consistency. Finally, a 3D-aware texture completion model combined with a texture enhancement model is used to generate seamless, high-resolution texture maps. Comprehensive experiments demonstrate that our framework significantly outperforms state-of-the-art methods in both flexibility and generation quality.
Key facts. Cited by 8 papers in the map (data through 14 Oct 2026). Placed in 3D, point cloud and scene generation, one of 14 directions in Diffusion models. Builds on 62 of its 70 references that are in the map. First posted on arXiv 3 Jun 2025.
Builds on
62 of 70 references.
Closest ancestors · 25
Same direction, newest first
- 2024Make-A-Texture: Fast Shape-Aware Texture Generation in 3 Seconds10 Dec
- 2024TEXGen: a Generative Diffusion Model for Mesh Textures22 Nov
- 2024FlexiTex: Enhancing Texture Generation via Visual Guidance19 Sep
- 2024TexGen: Text-Guided 3D Texture Generation with Multi-view Sampling and Resampling2 Aug
- 2024VCD-Texture: Variance Alignment based 3D-2D Co-Denoising for Text-Guided Texturing5 Jul
- 2024Unique3D: High-Quality and Efficient 3D Mesh Generation from a Single Image30 May
- 2024TexPainter: Generative Mesh Texturing with Multi-view Consistency17 May
- 2024GenesisTex: Adapting Image Denoising Diffusion to Texture Space26 Mar
- 2024SV3D: Novel Multi-view Synthesis and 3D Generation from a Single Image using Latent Video Diffusion18 Mar
- 2023Paint3D: Paint Anything 3D with Lighting-Less Texture Diffusion Models21 Dec
- 2023ImageDream: Image-Prompt Multi-view Diffusion for 3D Generation2 Dec
- 2023Zero123++: a Single Image to Consistent Multi-view Diffusion Base Model23 Oct
13 more
- 2023Wonder3D: Single Image to 3D using Cross-Domain Diffusion23 Oct
- 2023TexFusion: Synthesizing 3D Textures with Text-Guided Image Diffusion Models20 Oct
- 2023Consistent123: Improve Consistency for One Image to 3D Object Synthesis12 Oct
- 2023Consistent-1-to-3: Consistent Image to 3D View Synthesis via Geometry-aware Diffusion Models4 Oct
- 2023SyncDreamer: Generating Multiview-consistent Images from a Single-view Image7 Sep
- 2023MVDream: Multi-view Diffusion for 3D Generation31 Aug
- 2023Texture Generation on 3D Meshes with Point-UV Diffusion21 Aug
- 2023Fantasia3D: Disentangling Geometry and Appearance for High-quality Text-to-3D Content Creation24 Mar
- 2023Text2Tex: Text-driven Texture Synthesis via Diffusion Models20 Mar
- 2023Zero-1-to-3: Zero-shot One Image to 3D Object20 Mar
- 2023TEXTure: Text-Guided Texturing of 3D Shapes3 Feb
- 2022Magic3D: High-Resolution Text-to-3D Content Creation18 Nov
- 2022DreamFusion: Text-to-3D using 2D Diffusion29 Sep
Other references · 37
- 2021Learning Transferable Visual Models From Natural Language Supervisioncited by 33,744
- 2020An Image is Worth 16x16 Words: Transformers for Image Recognition at Scalecited by 30,186
- 2021High-Resolution Image Synthesis with Latent Diffusion Modelscited by 18,863
- 2019Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformercited by 14,599
- 2021LoRA: Low-Rank Adaptation of Large Language Modelscited by 14,380
- 2022Hierarchical Text-Conditional Image Generation with CLIP Latentscited by 6,585
- 2022Photorealistic Text-to-Image Diffusion Models with Deep Language Understandingcited by 6,355
- 2022Classifier-Free Diffusion Guidancecited by 5,847
- 2022Flow Matching for Generative Modelingcited by 5,702
- 2022Generative Adversarial Networkscited by 5,627
- 2023SDXL: Improving Latent Diffusion Models for High-Resolution Image Synthesiscited by 4,356
- 2024Scaling Rectified Flow Transformers for High-Resolution Image Synthesiscited by 4,181
25 more
- 2019Analyzing and Improving the Image Quality of StyleGANcited by 3,588
- 2022DreamBooth: Fine Tuning Text-to-Image Diffusion Models for Subject-Driven Generationcited by 3,300
- 2022An Image is Worth One Word: Personalizing Text-to-Image Generation using Textual Inversioncited by 2,245
- 2022Objaverse: A Universe of Annotated 3D Objectscited by 1,540
- 2023IP-Adapter: Text Compatible Image Prompt Adapter for Text-to-Image Diffusion Modelscited by 1,464
- 2018Demystifying MMD GANscited by 1,293
- 2021Real-ESRGAN: Training Real-World Blind Super-Resolution with Pure Synthetic Datacited by 970
- 2022Google Scanned Objects: A High-Quality Dataset of 3D Scanned Household Itemscited by 612
- 2023Point Transformer V3: Simpler, Faster, Strongercited by 589
- 2022Latent-NeRF for Shape-Guided Generation of 3D Shapes and Texturescited by 506
- 2023DMV3D: Denoising Multi-View Diffusion using 3D Large Reconstruction Modelcited by 214
- 2019Texture Fields: Learning Texture Representations in Function Spacecited by 210
- 2023Text-Guided Texturing by Synchronized Multi-View Diffusioncited by 86
- 2024IM-3D: Iterative Multiview Diffusion and Reconstruction for High-Quality 3D Generationcited by 84
- 2022Texturify: Generating Textures on 3D Shape Surfacescited by 65
- 2024FlashTex: Fast Relightable Mesh Texturing with LightControlNetcited by 56
- 2024TextureDreamer: Image-guided Texture Synthesis through Geometry-aware Diffusioncited by 52
- 2024Meta 3D TextureGen: Fast and Consistent Texture Generation for 3D Objectscited by 52
- 2023Instant-3D: Instant Neural Radiance Field Training Towards On-Device AR/VR 3D Reconstructioncited by 51
- 2024MVPaint: Synchronized Multi-View Diffusion for Painting Anything 3Dcited by 34
- 2023Mesh2Tex: Generating Mesh Textures from Image Queriescited by 31
- 2024StyleTex: Style Image-Guided Texture Generation for 3D Modelscited by 14
- 2023TUVF: Learning Generalizable Texture UV Radiance Fieldscited by 9
- 2024TexRO: Generating Delicate Textures of 3D Models by Recursive Optimizationcited by 9
- 2024FlexGen: Flexible Multi-View Generation from Text and Image Inputscited by 8
Built on by
Citing papers per year: 2025: 1; 2026: 7.
8 papers.
- 2025LaFiTe: A Generative Latent Field for 3D Native Texturingcited by 4
- 2026Hitem3D 2.0: Multi-View Guided Native 3D Texture Generationcited by 2
- 2026MV2UV: Generating High-quality UV Texture Maps with Multiview Promptscited by 1
- 2026Variational Test-time Optimization for Diffusion Synchronizationcited by 0
- 2026Accelerated Likelihood Maximization for Diffusion-based Versatile Content Generationcited by 0
- 2026GLOSS: Geometric Local Self-Similarity Learning for Faithful Reference-Guided Texture Fillcited by 0
- 2026DirectUV: Image-Conditioned UV Texture Generation with Surface-Aware Positional Encodingcited by 0
- 2026DynaMesh: Dynamic 3D Texture Generationcited by 0
- 2026DynaMesh: Dynamic 3D Texture Generation4 Oct 2026
- 2026DirectUV: Image-Conditioned UV Texture Generation with Surface-Aware Positional Encoding28 Sep 2026
- 2026GLOSS: Geometric Local Self-Similarity Learning for Faithful Reference-Guided Texture Fill26 Aug 2026
- 2026Accelerated Likelihood Maximization for Diffusion-based Versatile Content Generation30 Jun 2026
- 2026Variational Test-time Optimization for Diffusion Synchronization14 Jun 2026
- 2026Hitem3D 2.0: Multi-View Guided Native 3D Texture Generation10 Apr 2026
- 2026MV2UV: Generating High-quality UV Texture Maps with Multiview Prompts16 Mar 2026
- 2025LaFiTe: A Generative Latent Field for 3D Native Texturing4 Dec 2025
Similar, not cited
Close in wording, no citation either way
- 2024RoCoTex: A Robust Method for Consistent Texture Synthesis with Diffusion Models
- 2024FlexiDreamer: Single Image-to-3D Generation with FlexiCubes
- 2024Flex3D: Feed-Forward 3D Generation with Flexible Reconstruction Model and Input View Curation
- 2025MVPainter: Accurate and Detailed 3D Texture Generation via Multi-View Diffusion with Geometric Control
- 2024Infinite Texture: Text-guided High Resolution Diffusion Texture Synthesis
- 2025Step1X-3D: Towards High-Fidelity and Controllable Generation of Textured 3D Assets
- 2024GenesisTex2: Stable, Consistent and High-Quality Text-to-Texture Generation
- 2025UniTEX: Universal High Fidelity Generative Texturing for 3D Shapes