VideoMatGen: PBR Materials through Joint Generative Modeling
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arXiv
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| Main Authors: | , , , |
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| Format: | Preprint |
| Published: |
2026
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| _version_ | 1866912971060412416 |
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| author | Hasselgren, Jon Zeng, Zheng Hasan, Milos Munkberg, Jacob |
| author_facet | Hasselgren, Jon Zeng, Zheng Hasan, Milos Munkberg, Jacob |
| contents | We present a method for generating physically-based materials for 3D shapes based on a video diffusion transformer architecture. Our method is conditioned on input geometry and a text description, and jointly models multiple material properties (base color, roughness, metallicity, height map) to form physically plausible materials. We further introduce a custom variational auto-encoder which encodes multiple material modalities into a compact latent space, which enables joint generation of multiple modalities without increasing the number of tokens. Our pipeline generates high-quality materials for 3D shapes given a text prompt, compatible with common content creation tools. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2603_16566 |
| institution | arXiv |
| publishDate | 2026 |
| record_format | arxiv |
| spellingShingle | VideoMatGen: PBR Materials through Joint Generative Modeling Hasselgren, Jon Zeng, Zheng Hasan, Milos Munkberg, Jacob Computer Vision and Pattern Recognition Graphics We present a method for generating physically-based materials for 3D shapes based on a video diffusion transformer architecture. Our method is conditioned on input geometry and a text description, and jointly models multiple material properties (base color, roughness, metallicity, height map) to form physically plausible materials. We further introduce a custom variational auto-encoder which encodes multiple material modalities into a compact latent space, which enables joint generation of multiple modalities without increasing the number of tokens. Our pipeline generates high-quality materials for 3D shapes given a text prompt, compatible with common content creation tools. |
| title | VideoMatGen: PBR Materials through Joint Generative Modeling |
| topic | Computer Vision and Pattern Recognition Graphics |
| url | https://arxiv.org/abs/2603.16566 |