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arXiv · 2312.02970

Alchemist: Parametric Control of Material Properties with Diffusion Models

Prafull Sharma·Varun Jampani·Yuanzhen Li·Xuhui Jia·Dmitry Lagun·Fredo Durand·William T. Freeman·Mark Matthews
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Abstract

We propose a method to control material attributes of objects like roughness, metallic, albedo, and transparency in real images. Our method capitalizes on the generative prior of text-to-image models known for photorealism, employing a scalar value and instructions to alter low-level material properties. Addressing the lack of datasets with controlled material attributes, we generated an object-centric synthetic dataset with physically-based materials. Fine-tuning a modified pre-trained text-to-image model on this synthetic dataset enables us to edit material properties in real-world images while preserving all other attributes. We show the potential application of our model to material edited NeRFs.

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Prafull Sharma, Varun Jampani, Yuanzhen Li, Xuhui Jia, Dmitry Lagun, Fredo Durand, William T. Freeman, Mark Matthews. 2023-12-05. Alchemist: Parametric Control of Material Properties with Diffusion Models. https://arxiv.org/abs/2312.02970

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