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GeoCode: Interpretable Shape Programs

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arxiv 2212.11715 v2 pith:UQRYRG2H submitted 2022-12-19 cs.GR

classification cs.GR
keywords programsproceduralshapeshapesblocksbuildinggeocodegeometric
verification ladder T0 review T1 audit T2 compute T3 formal
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The task of crafting procedural programs capable of generating structurally valid 3D shapes easily and intuitively remains an elusive goal in computer vision and graphics. Within the graphics community, generating procedural 3D models has shifted to using node graph systems. They allow the artist to create complex shapes and animations through visual programming. Being a high-level design tool, they made procedural 3D modeling more accessible. However, crafting those node graphs demands expertise and training. We present GeoCode, a novel framework designed to extend an existing node graph system and significantly lower the bar for the creation of new procedural 3D shape programs. Our approach meticulously balances expressiveness and generalization for part-based shapes. We propose a curated set of new geometric building blocks that are expressive and reusable across domains. We showcase three innovative and expressive programs developed through our technique and geometric building blocks. Our programs enforce intricate rules, empowering users to execute intuitive high-level parameter edits that seamlessly propagate throughout the entire shape at a lower level while maintaining its validity. To evaluate the user-friendliness of our geometric building blocks among non-experts, we conducted a user study that demonstrates their ease of use and highlights their applicability across diverse domains. Empirical evidence shows the superior accuracy of GeoCode in inferring and recovering 3D shapes compared to an existing competitor. Furthermore, our method demonstrates superior expressiveness compared to alternatives that utilize coarse primitives. Notably, we illustrate the ability to execute controllable local and global shape manipulations.

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Cited by 2 Pith papers

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  1. Blended Point Cloud Diffusion for Localized Text-guided Shape Editing

    cs.GR 2025-07 conditional novelty 6.0 of 10

    BlendedPC fine-tunes Point-E for text-guided point cloud inpainting and uses an inference-time coordinate blending scheme that preserves identity outside the edited region.

  2. A Solver-Aided Hierarchical Language for LLM-Driven CAD Design

    cs.CV 2025-02 conditional novelty 6.0 of 10

    A solver-aided hierarchical DSL lets an untuned LLM generate precise, editable 2D CAD geometry from text prompts, outperforming OpenSCAD slightly on CLIP alignment.

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