Material Anything is a diffusion-based framework for generating physically-based rendering (PBR) materials for any 3D object, including texture-less, albedo-only, generated, and scanned models. It addresses the need for a unified, end-to-end solution for material generation across diverse lighting conditions and object types, benefiting researchers and developers in computer graphics and 3D content creation.

How It Works

The framework leverages a pre-trained diffusion model enhanced with a triple-head architecture and a rendering loss for improved stability and material quality. It utilizes confidence masks as a dynamic switcher within the diffusion model to effectively handle both textured and texture-less objects under varying lighting. A progressive material generation strategy guided by these masks, followed by a UV-space material refiner, ensures consistent, UV-ready material outputs.

Quick Start & Requirements

• Install Blender: Requires Blender 3.2.2 (recommended) or a compatible newer version. Installation instructions and download links are provided.
• Rendering: Scripts are available for rendering multi-view and UV-space material maps.
• Distributed Rendering: A script is provided for large-scale rendering, configurable via parameters like --num_gpus, --workers_per_gpu, and --timeout.
• Prerequisites: Ensure Blender binary is added to the system's PATH.

Highlighted Details

• Introduces the Material3D Dataset: 80K+ curated 3D objects with high-quality material maps and text descriptions.
• Handles texture-less, albedo-only, generated, and scanned objects.
• Outperforms existing methods across various object categories and lighting conditions.
• Provides a unified, automated, end-to-end diffusion framework.

Maintenance & Community

• Project is associated with CVPR 2025 Highlight.
• The paper is available via arXiv.

Licensing & Compatibility

• The repository is released under the MIT License.
• Compatible with commercial use and closed-source linking.

Limitations & Caveats

• Blender 3.2.2 is recommended; newer versions may have compatibility issues due to node name changes.
• The project is presented as a research artifact, with potential for further development and refinement.