[
    {
        "id": "osp-16294",
        "type": "article-journal",
        "title": "CADForge: Agentic Single-View CAD Reconstruction with Explicit Geometry Reasoning",
        "author": [
            {
                "family": "Lu",
                "given": "Keyang"
            },
            {
                "family": "Yang",
                "given": "Zhifei"
            },
            {
                "family": "Dong",
                "given": "Tianao"
            },
            {
                "family": "Xing",
                "given": "Mingzhe"
            },
            {
                "family": "Xiao",
                "given": "Zhen"
            },
            {
                "family": "Wang",
                "given": "Yikai"
            }
        ],
        "URL": "https://omanscience.com/ar/articles/cadforge-agentic-single-view-cad-reconstruction-with-explicit-geometry-reasoning",
        "language": "en",
        "issued": {
            "date-parts": [
                [
                    2026
                ]
            ]
        },
        "abstract": "Reconstructing editable parametric CAD models from a single-view image is of great practical value for modern manufacturing, yet remains challenging due to incomplete geometric observations and complex inter-part relationships. To address it, we propose CADForge, an agentic framework that progressively converts a single image into CadQuery programs. CADForge decomposes an object into CAD-meaningful components and performs explicit geometric reasoning for each component, a process that first identifies CAD-relevant constraints and then translates them into precise modeling parameters through mathematical code. The inferred parameters then drive component-wise synthesis of executable CadQuery programs, with a review agent evaluating the resulting geometry and providing targeted feedback for iterative refinement. To further improve robustness and efficiency, CADForge incorporates a failure-guided toolkit construction mechanism to distill accumulated experience into tools, and maintains a compact parametric CAD memory for retrieving modeling context on demand. Experiments on diverse single- and multi-part objects show that CADForge consistently outperforms existing baselines in reconstruction fidelity and perceptual quality, demonstrating an effective approach to accurate single-view CAD reconstruction."
    }
]