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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\n            <jats:italic>Fusion 360 Gallery<\/jats:italic>\n            , consisting of a simple language with just the\n            <jats:italic>sketch<\/jats:italic>\n            and\n            <jats:italic>extrude<\/jats:italic>\n            modeling operations, and a dataset of 8,625 human design sequences expressed in this language. We also present an interactive environment called the\n            <jats:italic>Fusion 360 Gym<\/jats:italic>\n            , 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.\n          <\/jats:p>","DOI":"10.1145\/3450626.3459818","type":"journal-article","created":{"date-parts":[[2021,7,20]],"date-time":"2021-07-20T00:04:27Z","timestamp":1626739467000},"page":"1-24","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":160,"title":["Fusion 360 gallery"],"prefix":"10.1145","volume":"40","author":[{"given":"Karl D. 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