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Graph."],"published-print":{"date-parts":[[2022,12]]},"abstract":"<jats:p>The trade-off between speed and fidelity in cloth simulation is a fundamental computational problem in computer graphics and computational design. Coarse cloth models provide the interactive performance required by designers, but they can not be simulated at higher resolutions (\"up-resed\") without introducing simulation artifacts and\/or unpredicted outcomes, such as different folds, wrinkles and drapes. But how can a coarse simulation predict the result of an unconstrained, high-resolution simulation that has not yet been run?<\/jats:p>\n          <jats:p>\n            We propose Progressive Cloth Simulation (PCS), a new forward simulation method for efficient\n            <jats:italic>preview<\/jats:italic>\n            of cloth quasistatics on exceedingly coarse triangle meshes with consistent and progressive improvement over a hierarchy of increasingly higher-resolution models. PCS provides an efficient coarse previewing simulation method that predicts the coarse-scale folds and wrinkles that will be generated by a corresponding converged, high-fidelity C-IPC simulation of the cloth drape's equilibrium. For each preview PCS can generate an increasing-resolution sequence of\n            <jats:italic>consistent<\/jats:italic>\n            models that progress towards this converged solution. This successive improvement can then be interrupted at any point, for example, whenever design parameters are updated. PCS then ensures feasibility at all resolutions, so that predicted solutions remain intersection-free and capture the complex folding and buckling behaviors of frictionally contacting cloth.\n          <\/jats:p>","DOI":"10.1145\/3550454.3555510","type":"journal-article","created":{"date-parts":[[2022,11,30]],"date-time":"2022-11-30T21:19:07Z","timestamp":1669843147000},"page":"1-16","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":19,"title":["Progressive Simulation for Cloth Quasistatics"],"prefix":"10.1145","volume":"41","author":[{"given":"Jiayi Eris","family":"Zhang","sequence":"first","affiliation":[{"name":"Adobe &amp; Stanford University"}]},{"given":"J\u00e9r\u00e9mie","family":"Dumas","sequence":"additional","affiliation":[{"name":"Adobe"}]},{"given":"Yun (Raymond)","family":"Fei","sequence":"additional","affiliation":[{"name":"Adobe"}]},{"given":"Alec","family":"Jacobson","sequence":"additional","affiliation":[{"name":"Adobe &amp; University of Toronto, Canada"}]},{"given":"Doug L.","family":"James","sequence":"additional","affiliation":[{"name":"Stanford University"}]},{"given":"Danny M.","family":"Kaufman","sequence":"additional","affiliation":[{"name":"Adobe"}]}],"member":"320","published-online":{"date-parts":[[2022,11,30]]},"reference":[{"key":"e_1_2_2_1_1","doi-asserted-by":"publisher","DOI":"10.1145\/2897824.2925884"},{"key":"e_1_2_2_2_1","doi-asserted-by":"publisher","DOI":"10.1145\/280814.280821"},{"key":"e_1_2_2_3_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.cag.2013.08.003"},{"key":"e_1_2_2_4_1","doi-asserted-by":"publisher","DOI":"10.1145\/1276377.1276439"},{"key":"e_1_2_2_5_1","volume-title":"Parallel Algorithms in Computational Science and Engineering","author":"Bollh\u00f6fer Matthias","unstructured":"Matthias Bollh\u00f6fer, Olaf Schenk, Radim Janalik, Steve Hamm, and Kiran Gullapalli. 2020. 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