Demonstration of Style2Fab: Functionality-Aware Segmentation for Fabricating Personalized 3D Models with Generative AI
Authors: 
Faraz Faruqi, Ahmed Katary, Tarik Hasic, Amira Abdel-Rahman, Nayeemur Rahman, Leandra Tejedor, Mackenzie Leake, 
Megan Hofmann, 
Stefanie MuellerAuthors Info & Claims
Article No.: 98, Pages 1 - 5
Abstract
With recent advances in Generative AI, it is becoming easier to automatically manipulate 3D models. However, current methods tend to apply edits to models globally, which risks compromising the intended functionality of the 3D model when fabricated in the physical world. For example, modifying functional segments in 3D models, such as the base of a vase, could break the original functionality of the model, thus causing the vase to fall over. We introduce Style2Fab, a system for automatically segmenting 3D models into functional and aesthetic elements, and selectively modifying the aesthetic segments, without affecting the functional segments. Style2Fab uses a semi-automatic classification method to decompose 3D models into functional and aesthetic elements, and differentiable rendering to selectively stylize the functional segments. We demonstrate the functionality of this tool with six application examples across domains of Home Interior Design, Medical Applications, and Personal Accessories.
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Published In
October 2023
424 pages
ISBN:9798400700965
DOI:10.1145/3586182
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Published: 29 October 2023
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UIST '23: The 36th Annual ACM Symposium on User Interface Software and Technology
October 29 - November 1, 2023
CA, San Francisco, USA
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