mlsanityData to 7 Oct 2026

MuMA: 3D PBR Texturing via Multi-Channel Multi-View Generation and Agentic Post-Processing

arXiv 2503.18461 ↗First posted 24 Mar 2025cs.CVcited by 8

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Abstract (arXiv)

Current methods for 3D generation still fall short in physically based rendering (PBR) texturing, primarily due to limited data and challenges in modeling multi-channel materials. In this work, we propose MuMA, a method for 3D PBR texturing through Multi-channel Multi-view generation and Agentic post-processing. Our approach features two key innovations: 1) We opt to model shaded and albedo appearance channels, where the shaded channels enables the integration intrinsic decomposition modules for material properties. 2) Leveraging multimodal large language models, we emulate artists' techniques for material assessment and selection. Experiments demonstrate that MuMA achieves superior results in visual quality and material fidelity compared to existing methods.

Key facts. Cited by 8 papers in the map (data through 7 Oct 2026). Builds on 56 of its 59 references that are in the map. First posted on arXiv 24 Mar 2025.

Builds on

56 of 59 references.

References · 56

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38 more
  1. 2022RePaint: Inpainting using Denoising Diffusion Probabilistic Modelscited by 1,419
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  13. 2023TEXTure: Text-Guided Texturing of 3D Shapescited by 303
  14. 2023Text2Tex: Text-driven Texture Synthesis via Diffusion Modelscited by 234
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  17. 2023Paint3D: Paint Anything 3D with Lighting-Less Texture Diffusion Modelscited by 122
  18. 2024CraftsMan3D: High-fidelity Mesh Generation with 3D Native Generation and Interactive Geometry Refinercited by 120
  19. 2024MV-Adapter: Multi-view Consistent Image Generation Made Easycited by 111
  20. 2023TexFusion: Synthesizing 3D Textures with Text-Guided Image Diffusion Modelscited by 86
  21. 2023Text-Guided Texturing by Synchronized Multi-View Diffusioncited by 86
  22. 2023Paint-it: Text-to-Texture Synthesis via Deep Convolutional Texture Map Optimization and Physically-Based Renderingcited by 84
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  38. 2024Make-it-Real: Unleashing Large Multimodal Model for Painting 3D Objects with Realistic Materialscited by 17

50 most cited of 56 All 56 (JSON)

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2025: 6; 2026: 2.

8 papers.

  1. 2025MAR-3D: Progressive Masked Auto-regressor for High-Resolution 3D Generationcited by 11
  2. 2025GarmentX: Autoregressive Parametric Representations for High-Fidelity 3D Garment Generationcited by 3
  3. 2025CaliTex: Geometry-Calibrated Attention for View-Coherent 3D Texture Generationcited by 3
  4. 2025Large Material Gaussian Model for Relightable 3D Generationcited by 2
  5. 2025LumiTex: Towards High-Fidelity PBR Texture Generation with Illumination Contextcited by 2
  6. 2025MatLat: Material Latent Space for PBR Texture Generationcited by 1
  7. 2026AssetFormer: Modular 3D Assets Generation with Autoregressive Transformercited by 1
  8. 2026MV2UV: Generating High-quality UV Texture Maps with Multiview Promptscited by 0

Similar, not cited

Close in wording, no citation either way

  1. 2025PBR3DGen: A VLM-guided Mesh Generation with High-quality PBR Texture
  2. 2025MatPedia: A Universal Generative Foundation for High-Fidelity Material Synthesis
  3. 2025MatCLIP: Light- and Shape-Insensitive Assignment of PBR Material Models
  4. 2026Toward Richer Material Generation via Procedural Data Enhancement
  5. 2025Chord: Chain of Rendering Decomposition for PBR Material Estimation from Generated Texture Images
  6. 2024MatAtlas: Text-driven Consistent Geometry Texturing and Material Assignment
  7. 2024DreamPBR: Text-driven Generation of High-resolution SVBRDF with Multi-modal Guidance
  8. 2026Home3D 1.0: A High-Fidelity Image-to-3D Asset Generation System for Interior Design