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3-D Material Style Transfer for Reconstructing Unknown Appearance in Complex Natural Materials

arXiv 2112.15589 ↗First posted 31 Dec 2021cs.CVcited by 0

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Abstract (arXiv)

We propose a 3-D material style transfer framework for reconstructing invisible (or faded) appearance properties in complex natural materials. Our algorithm addresses the technical challenge of transferring appearance properties from one object to another of the same material when both objects have intricate, noncorresponding color patterns. Eggshells, exoskeletons, and minerals, for example, have patterns composed of highly randomized layers of organic and inorganic compounds. These materials pose a challenge as the distribution of compounds that determine surface color changes from object to object and within local pattern regions. Our solution adapts appearance observations from a material property distribution in an exemplar to the material property distribution of a target object to reconstruct its unknown appearance. We use measured reflectance in 3-D bispectral textures to record changing material property distributions. Our novel implementation of spherical harmonics uses principles from chemistry and biology to learn relationships between color (hue and saturation) and material composition and concentration in an exemplar. The encoded relationships are transformed to the property distribution of a target for color recovery and material assignment. Quantitative and qualitative evaluation methods show that we replicate color patterns more accurately than methods that only rely on shape correspondences and coarse-level perceptual differences. We demonstrate applications of our work for reconstructing color in extinct fossils, restoring faded artifacts and generating synthetic textures.

Key facts. No citing papers in the map yet (data through 14 Oct 2026). Builds on 3 of its 72 references that are in the map. First posted on arXiv 31 Dec 2021.

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3 of 72 references.

References · 3

  1. 2016Texture Networks: Feed-forward Synthesis of Textures and Stylized Imagescited by 174
  2. 2017Building Data-driven Models with Microstructural Images: Generalization and Interpretabilitycited by 2
  3. 2021Non-Photorealistic Rendering of Layered Materials: A Multispectral Approachcited by 1

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