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VideoMat: Extracting PBR Materials from Video Diffusion Models

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We leverage finetuned video diffusion models, intrinsic decomposition of videos, and physically-based differentiable rendering to generate high quality materials for 3D models given a text prompt or a single image. We condition a video diffusion model to respect the input geometry and lighting condition. This model produces multiple views of a given 3D model with coherent material properties. Secondly, we use a recent model to extract intrinsics (base color, roughness, metallic) from the generated video. Finally, we use the intrinsics alongside the generated video in a differentiable path tracer to robustly extract PBR materials directly compatible with common content creation tools.

Jacob Munkberg, Zian Wang, Ruofan Liang, Tianchang Shen, Jon Hasselgren• 2025

Related benchmarks

TaskDatasetResultRank
Material generationBlenderVault (test)
CLIP-FID5.64
8
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