CRAFT: Designing Creative and Functional 3D Objects

For designing a wide range of everyday objects, the design process should be aware of both the human body and the underlying semantics of the design specification. However, these two objectives present significant challenges to the current AI-based designing tools. In this work, we present a method to synthesize body-aware 3D objects from a base mesh given an input body geometry and either text or image as guidance. The generated objects can be simulated on virtual characters, or fabricated for real-world use. We propose to use a mesh deformation procedure that optimizes for both semantic alignment as well as contact and penetration losses. Using our method, users can generate both virtual or real-world objects from text, image, or sketch, without the need for manual artist intervention. We present both qualitative and quantitative results on various object categories, demonstrating the effectiveness of our approach.

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Publication Details

Published
2025-02-26
DOI
https://doi.org/10.1109/wacv61041.2025.00701
Citations
1
Primary Topic
3D Surveying and Cultural Heritage
Type
article
Field-Weighted Citation Impact
2.35

Funders

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article

CRAFT: Designing Creative and Functional 3D Objects

Michelle Guo, Hannah Cha, Jiajun Wu, Ruohan Zhang et al.
1 citations
3D Surveying and Cultural Heritage
2.35
article

CRAFT: Designing Creative and Functional 3D Objects

Michelle Guo, Hannah Cha, Jiajun Wu, Ruohan Zhang, C. Karen Liu, Mia Tang
article en
1 citations

Abstract

For designing a wide range of everyday objects, the design process should be aware of both the human body and the underlying semantics of the design specification. However, these two objectives present significant challenges to the current AI-based designing tools. In this work, we present a method to synthesize body-aware 3D objects from a base mesh given an input body geometry and either text or image as guidance. The generated objects can be simulated on virtual characters, or fabricated for real-world use. We propose to use a mesh deformation procedure that optimizes for both semantic alignment as well as contact and penetration losses. Using our method, users can generate both virtual or real-world objects from text, image, or sketch, without the need for manual artist intervention. We present both qualitative and quantitative results on various object categories, demonstrating the effectiveness of our approach.

Stanford University (US)
National Science Foundation
Openalex Percentile: Top 15%
3D Surveying and Cultural Heritage
2.35
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