The Mokume Dataset and Inverse Modeling of Solid Wood Textures
Maria Larsson, Hodaka Yamaguchi, Ehsan Pajouheshgar, I-Chao Shen, Kenji Tojo, Chia-Ming Chang, Lars Hansson, Olof Broman, Takashi Ijiri, Ariel Shamir, Wenzel Jakob, and Takeo Igarashi
Maria Larsson, Hodaka Yamaguchi, Ehsan Pajouheshgar, I-Chao Shen, Kenji Tojo, Chia-Ming Chang, Lars Hansson, Olof Broman, Takashi Ijiri, Ariel Shamir, Wenzel Jakob, and Takeo Igarashi
We present the Mokume dataset for solid wood texturing consisting of 190 cube-shaped samples of various hard and softwood species documented by high-resolution exterior photographs, annual ring annotations, and volumetric computed tomography (CT) scans. A subset of samples further includes photographs along slanted cuts through the cube for validation purposes. Using this dataset, we propose a three-stage inverse modeling pipeline to infer solid wood textures using only exterior photographs. Our method begins by evaluating a neural model to localize year rings on the cube face photographs. We then extend these exterior 2D observations into a globally consistent 3D representation by optimizing a procedural growth field using a novel iso-contour loss. Finally, we synthesize a detailed volumetric color texture from the growth field. For this last step, we propose two methods with different efficiency and quality characteristics: a fast inverse procedural texture method, and a neural cellular automaton (NCA). We demonstrate the synergy between the Mokume dataset and the proposed algorithms through comprehensive comparisons with unseen captured data. We also present experiments demonstrating the efficiency of our pipeline's components against ablations and baselines.
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Maria Larsson, The University of Tokyo
Hodaka Yamaguchi, Gifu Prefectural Research Institute for Human Life Technology and Nihon University
Ehsan Pajouheshgar, École Polytechnique Féderale de Lausanne (EPFL)
I-Chao Shen, The University of Tokyo
Kenji Tojo, The University of Tokyo
Chia-Ming Chang, National Taiwan University of Arts
Lars Hansson, Luleå University of Technology and Norwegian University of Science and Technology
Olof Broman, Luleå University of Technology
Takashi Ijiri, Shibaura Institute of Technology
Ariel Shamir, Reichman University
Wenzel Jakob, The University of Tokyo and École Polytechnique Féderale de Lausanne (EPFL)
Takeo Igarashi, The University of Tokyo
Maria Larsson, Hodaka Yamaguchi, Ehsan Pajouheshgar, I-Chao Shen, Kenji Tojo, Chia-Ming Chang, Lars Hansson, Olof Broman, Takashi Ijiri, Ariel Shamir, Wenzel Jakob, and Takeo Igarashi. 2025. The Mokume Dataset and Inverse Modeling of Solid Wood Textures. ACM Trans. Graph. 44, 4 (August 2025), 18 pages. https://doi.org/10.1145/3730874
