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Updated: Feb 25, 2026

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OmniSketch: Sketch-Guided Text-to-3D Generation With High-Fidelity Geometry and Texture.

Xinbin Sun, Zhentong Xu, Guodong Wang

    IEEE Computer Graphics and Applications
    |February 23, 2026
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    Summary
    This summary is machine-generated.

    OmniSketch generates 3D models from sketches and text by using a three-stage pipeline. This novel framework enhances 3D content creation with improved geometric fidelity and texture consistency.

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    Area of Science:

    • Computer Vision
    • 3D Graphics
    • Artificial Intelligence

    Background:

    • Digitalization relies on rapid 3D content generation from abstract concepts.
    • Challenges in sketch-based and text-to-3D generation include sparse input, lack of texture, and dataset misalignment.

    Purpose of the Study:

    • Introduce OmniSketch, a framework for sketch-guided text-to-3D generation.
    • Address limitations in current cross-modal 3D synthesis.
    • Improve geometric fidelity and texture consistency in generated 3D models.

    Main Methods:

    • A three-stage pipeline: conditional diffusion for reference view generation, Rectified Flow for high-fidelity geometry, and geometry-guided synthesis for texturing.
    • Fusing sketch structural constraints with semantic descriptions.
    • Utilizing multi-view image synthesis for view-consistent textures.

    Main Results:

    • OmniSketch surpasses state-of-the-art methods in geometric accuracy and texture coherence.
    • Demonstrated superior performance in 3D model generation from sketches and text.
    • Successful construction of a multi-modal sketch-to-3D dataset and interactive platform.

    Conclusions:

    • The proposed OmniSketch framework effectively tackles challenges in sketch-guided 3D content generation.
    • The method achieves high-quality 3D models with accurate geometry and consistent textures.
    • OmniSketch facilitates advancements in digital content creation and interactive applications.