{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,3]],"date-time":"2026-07-03T08:15:44Z","timestamp":1783066544397,"version":"3.54.6"},"reference-count":54,"publisher":"Association for Computing Machinery (ACM)","issue":"4","license":[{"start":{"date-parts":[[2026,7,3]],"date-time":"2026-07-03T00:00:00Z","timestamp":1783036800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc-nd\/4.0\/legalcode"}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":["ACM Trans. Graph."],"published-print":{"date-parts":[[2026,7,3]]},"abstract":"<jats:p>\n                    Articulation modeling aims to infer movable parts and their motion parameters for a 3D object, enabling interactive animation, simulation, and shape editing. In this paper, we present\n                    <jats:italic toggle=\"yes\">Sketch2Arti<\/jats:italic>\n                    , the first\n                    <jats:italic toggle=\"yes\">sketch-based articulation modeling<\/jats:italic>\n                    system for CAD objects. Our key observation is that designers naturally communicate articulation intent through lightweight sketches (\n                    <jats:italic toggle=\"yes\">e.g.<\/jats:italic>\n                    , arrows and strokes) that indicate how parts should move, yet translating such sketches into articulated 3D models remains largely manual.\n                    <jats:italic toggle=\"yes\">Sketch2Arti<\/jats:italic>\n                    bridges this gap by enabling users to specify articulation through simple 2D sketches drawn from a chosen viewpoint. Given a CAD model and user sketches, our approach automatically discovers the corresponding movable parts and predicts their motion parameters, allowing iterative modeling of multiple articulations on complex objects with fine-grained control. Importantly,\n                    <jats:italic toggle=\"yes\">Sketch2Arti<\/jats:italic>\n                    is trained in a category-agnostic manner without requiring object category information, leading to strong generalization to diverse objects beyond existing articulation datasets. Moreover, for shell models lacking interior structures,\n                    <jats:italic toggle=\"yes\">Sketch2Arti<\/jats:italic>\n                    supports controllable internal completion guided by user sketches, generating plausible internal components consistent with the existing geometry and predicted motion constraints. Comprehensive experiments and user evaluations demonstrate the effectiveness, controllability, and generalization of\n                    <jats:italic toggle=\"yes\">Sketch2Arti.<\/jats:italic>\n                  <\/jats:p>\n                  <jats:p>The code, dataset, and the prototype system are at https:\/\/arlo-yang.github.io\/Sketch2Arti.<\/jats:p>","DOI":"10.1145\/3811375","type":"journal-article","created":{"date-parts":[[2026,7,3]],"date-time":"2026-07-03T07:05:51Z","timestamp":1783062351000},"page":"1-17","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":0,"title":["Sketch2Arti: Sketch-based Articulation Modeling of CAD Objects"],"prefix":"10.1145","volume":"45","author":[{"ORCID":"https:\/\/orcid.org\/0009-0007-4814-1733","authenticated-orcid":false,"given":"Yi","family":"Yang","sequence":"first","affiliation":[{"name":"University of Edinburgh, Edinburgh, United Kingdom"},{"name":"Tsinghua University, Edinburgh, United Kingdom"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3628-9777","authenticated-orcid":false,"given":"Hao","family":"Pan","sequence":"additional","affiliation":[{"name":"Tsinghua University, Beijing, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0006-7647-604X","authenticated-orcid":false,"given":"Yijing","family":"Cui","sequence":"additional","affiliation":[{"name":"Tsinghua University, Beijing, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9251-3716","authenticated-orcid":false,"given":"Alla","family":"Sheffer","sequence":"additional","affiliation":[{"name":"University of British Columbia, Vancouver, Canada"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0448-4957","authenticated-orcid":false,"given":"Changjian","family":"Li","sequence":"additional","affiliation":[{"name":"University of Edinburgh, Edinburgh, United Kingdom"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"320","published-online":{"date-parts":[[2026,7,3]]},"reference":[{"key":"e_1_2_2_1_1","doi-asserted-by":"publisher","DOI":"10.1017\/S0890060419000349"},{"key":"e_1_2_2_2_1","doi-asserted-by":"publisher","DOI":"10.1145\/3757377.3763845"},{"key":"e_1_2_2_3_1","doi-asserted-by":"publisher","DOI":"10.1145\/2897824.2925970"},{"key":"e_1_2_2_4_1","volume-title":"Samir Yitzhak Gadre, et al","author":"Deitke Matt","year":"2023","unstructured":"Matt Deitke, Ruoshi Liu, Matthew Wallingford, Huong Ngo, Oscar Michel, Aditya Kusupati, Alan Fan, Christian Laforte, Vikram Voleti, Samir Yitzhak Gadre, et al. 2023a. 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