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GenerativeSurface: GenAI-Assisted Semantic Scaffolding for 3D Conceptual Design in Mixed Reality.

Yichen Chai, Qianyuan Zou, Zihang Liu

    IEEE Transactions on Visualization and Computer Graphics
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    Generative Surface uses AI to turn natural language into 3D models, helping engineers overcome challenges in Mixed Reality (MR) design. This AI-powered tool streamlines the design process for better 3D sketching and concept realization.

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    Area of Science:

    • Engineering Design
    • Human-Computer Interaction
    • Artificial Intelligence

    Background:

    • Transitioning from 2D sketches to 3D models is a significant hurdle in engineering.
    • Mixed Reality (MR) offers potential for direct 3D creation but presents challenges like initiating designs and precise sketching.

    Purpose of the Study:

    • To introduce Generative Surface, an AI system designed to facilitate 3D sketching in MR environments.
    • To address the Initiation Challenge and Expression Challenge faced by designers in MR.

    Main Methods:

    • Leveraging AI to translate natural language descriptions into interactive 3D surfaces.
    • Implementing a "describe, generate, sketch, iterate" workflow for designers.
    • Conducting comparative evaluations against existing methods like primitive scaffolding and freehand sketching.

    Main Results:

    • Generative Surface effectively translates natural language into usable 3D surfaces for sketching.
    • The system addresses both the initiation and precise expression challenges in mid-air sketching.
    • Comparative evaluations show improved bridging of conceptual intent and 3D sketch expression.

    Conclusions:

    • Generative Surface transforms the engineering design workflow in immersive environments.
    • The AI-driven approach enhances the efficiency and effectiveness of 3D sketching in MR.
    • This method offers a promising solution for designers working with complex 3D concepts in MR.