3D-CoS: A New 3D Reconstruction Paradigm Based on VLM Code Synthesis
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Abstract (arXiv)
Most recent 3D reconstruction and editing systems operate on implicit and explicit representations such as NeRF, point clouds, or meshes. While these representations enable high-fidelity rendering, they are fundamentally low-level and hard to control programmatically. In contrast, we propose and systematically evaluate a new 3D reconstruction paradigm, 3D Code Synthesis (3D-CoS), where 3D assets are constructed as executable Blender code, a programmatic and interpretable medium. To assess how well current VLMs can use code to represent 3D objects, we evaluate representative open-source and closed-source VLMs in code-based reconstruction under a unified protocol. We further introduce a suite of structured code-synthesis workflows, including blueprint-based planning, Retrieval-Augmented Generation (RAG) over Blender API documentation, few-shot geometric demonstrations, and a component-level Agent workflow for part-wise code generation. To demonstrate the unique advantages of this representation, we further evaluate localized text-driven modifications and compare our code-based edits with a point-cloud-based 3D editing baseline. Our study shows that code as a 3D representation offers strong controllability and locality, yielding stronger edit fidelity and better preservation of unedited regions in our targeted editing evaluation. Our work also analyzes the potential of this paradigm, delineates the current capability frontier of VLMs for programmatic 3D modeling, and highlights code synthesis as a promising direction for editable 3D reconstruction.
Key facts. Cited by 1 paper in the map (data through 7 Oct 2026). Builds on 28 of its 42 references that are in the map. First posted on arXiv 9 Jun 2026.
Builds on
28 of 42 references.
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16 more
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- 2026Procedura: Agentic 3D Modeling with Procedural Control
- 2026Code4Scene: Benchmarking Coding Agents for Constructing and Editing 3D Scenes
- 20263D Primitives are a Spatial Language for VLMs
- 2026Judging to Improve: A De-biased VLM-as-3D-Judge Protocol for Single-Image 3D Generation