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Fusion 360 Gallery: A Dataset and Environment for Programmatic CAD Construction from Human Design Sequences

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arxiv 2010.02392 v2 pith:EN4YXMFP submitted 2020-10-05 cs.LG cs.CVcs.GR

classification cs.LGcs.CVcs.GR
keywords datasetdesignprogramenvironmentfusionconstructiongalleryhuman
verification ladder T0 review T1 audit T2 compute T3 formal
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Parametric computer-aided design (CAD) is a standard paradigm used to design manufactured objects, where a 3D shape is represented as a program supported by the CAD software. Despite the pervasiveness of parametric CAD and a growing interest from the research community, currently there does not exist a dataset of realistic CAD models in a concise programmatic form. In this paper we present the Fusion 360 Gallery, consisting of a simple language with just the sketch and extrude modeling operations, and a dataset of 8,625 human design sequences expressed in this language. We also present an interactive environment called the Fusion 360 Gym, which exposes the sequential construction of a CAD program as a Markov decision process, making it amendable to machine learning approaches. As a use case for our dataset and environment, we define the CAD reconstruction task of recovering a CAD program from a target geometry. We report results of applying state-of-the-art methods of program synthesis with neurally guided search on this task.

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Cited by 1 Pith paper

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score. OpenAlex reports about 9 citations worldwide. Full citation record

  1. GenCAD-Self-Repairing: Feasibility Enhancement for 3D CAD Generation

    cs.CV 2025-05 conditional novelty 5.0 of 10

    A self-repair framework raises GenCAD's feasible-CAD-generation rate from 93.1% to 97.0% by guiding diffusion with a validity classifier and a latent regressor, while slightly worsening geometry accuracy.

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