Presentation

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The Mokume Dataset and Inverse Modeling of Solid Wood Textures
SessionTextures, Tiles & Codes
DescriptionWe present the Mokume dataset for solid wood texturing, comprising nearly 190 samples from various species. Using this dataset, we propose an inverse modeling pipeline to infer volumetric wood textures from surface photographs, employing inverse procedural texturing and neural cellular automata (NCA).
Authors
Maria Larsson
The University of Tokyo
Hodaka Yamaguchi
Gifu Prefecture Research Institute for Human Life Technology
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
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
École Polytechnique Féderale de Lausanne (EPFL)
Takeo Igarashi
The University of Tokyo
Event Type
Technical Paper
TimeThursday, 14 August 20252:30pm - 2:40pm PDT
LocationWest Building, Rooms 211-214
ACM Digital Library Journal Papers' PDFs
Conference Papers' PDFs
Session Time & Location
Sunday, 10 August 20256:00pm - 8:45pm PDTWest Building, Ballroom AB
Thursday, 14 August 20252:00pm - 3:30pm PDTWest Building, Rooms 211-214
Recordings
Livestreamed
Recorded
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