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Article: Learning Part Generation and Assembly for Sketching Man-Made Objects

TitleLearning Part Generation and Assembly for Sketching Man-Made Objects
Authors
Keywordsmodelling
modelling interfaces
part assembly
Issue Date2021
PublisherWiley-Blackwell Publishing Ltd. The Journal's web site is located at http://onlinelibrary.wiley.com/journal/10.1111/%28ISSN%291467-8659
Citation
Computer Graphics Forum, 2021, v. 40 n. 1, p. 222-233 How to Cite?
AbstractModeling 3D objects on existing software usually requires a heavy amount of interactions, especially for users who lack basic knowledge of 3D geometry. Sketch-based modeling is a solution to ease the modelling procedure and thus has been researched for decades. However, modelling a man-made shape with complex structures remains challenging. Existing methods adopt advanced deep learning techniques to map holistic sketches to 3D shapes. They are still bottlenecked to deal with complicated topologies. In this paper, we decouple the task of sketch2shape into a part generation module and a part assembling module, where deep learning methods are leveraged for the implementation of both modules. By changing the focus from holistic shapes to individual parts, it eases the learning process of the shape generator and guarantees high-quality outputs. With the learned automated part assembler, users only need a little manual tuning to obtain a desired layout. Extensive experiments and user studies demonstrate the usefulness of our proposed system.
Persistent Identifierhttp://hdl.handle.net/10722/301457
ISSN
2020 Impact Factor: 2.078
2020 SCImago Journal Rankings: 0.578

 

DC FieldValueLanguage
dc.contributor.authorDu, D-
dc.contributor.authorZhu, H-
dc.contributor.authorNie, Y-
dc.contributor.authorHan, X-
dc.contributor.authorCui, S-
dc.contributor.authorYu, Y-
dc.contributor.authorLiu, L-
dc.date.accessioned2021-07-27T08:11:22Z-
dc.date.available2021-07-27T08:11:22Z-
dc.date.issued2021-
dc.identifier.citationComputer Graphics Forum, 2021, v. 40 n. 1, p. 222-233-
dc.identifier.issn0167-7055-
dc.identifier.urihttp://hdl.handle.net/10722/301457-
dc.description.abstractModeling 3D objects on existing software usually requires a heavy amount of interactions, especially for users who lack basic knowledge of 3D geometry. Sketch-based modeling is a solution to ease the modelling procedure and thus has been researched for decades. However, modelling a man-made shape with complex structures remains challenging. Existing methods adopt advanced deep learning techniques to map holistic sketches to 3D shapes. They are still bottlenecked to deal with complicated topologies. In this paper, we decouple the task of sketch2shape into a part generation module and a part assembling module, where deep learning methods are leveraged for the implementation of both modules. By changing the focus from holistic shapes to individual parts, it eases the learning process of the shape generator and guarantees high-quality outputs. With the learned automated part assembler, users only need a little manual tuning to obtain a desired layout. Extensive experiments and user studies demonstrate the usefulness of our proposed system.-
dc.languageeng-
dc.publisherWiley-Blackwell Publishing Ltd. The Journal's web site is located at http://onlinelibrary.wiley.com/journal/10.1111/%28ISSN%291467-8659-
dc.relation.ispartofComputer Graphics Forum-
dc.rightsSubmitted (preprint) Version This is the pre-peer reviewed version of the following article: [FULL CITE], which has been published in final form at [Link to final article using the DOI]. This article may be used for non-commercial purposes in accordance with Wiley Terms and Conditions for Use of Self-Archived Versions. Accepted (peer-reviewed) Version This is the peer reviewed version of the following article: [FULL CITE], which has been published in final form at [Link to final article using the DOI]. This article may be used for non-commercial purposes in accordance with Wiley Terms and Conditions for Use of Self-Archived Versions.-
dc.subjectmodelling-
dc.subjectmodelling interfaces-
dc.subjectpart assembly-
dc.titleLearning Part Generation and Assembly for Sketching Man-Made Objects-
dc.typeArticle-
dc.identifier.emailYu, Y: yzyu@cs.hku.hk-
dc.identifier.authorityYu, Y=rp01415-
dc.description.naturelink_to_subscribed_fulltext-
dc.identifier.doi10.1111/cgf.14184-
dc.identifier.scopuseid_2-s2.0-85097530575-
dc.identifier.hkuros323535-
dc.identifier.volume40-
dc.identifier.issue1-
dc.identifier.spage222-
dc.identifier.epage233-
dc.publisher.placeUnited Kingdom-

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