String-Based Synthesis of Structured Shapes

dc.contributor.authorKalojanov, Javoren_US
dc.contributor.authorLim, Isaaken_US
dc.contributor.authorMitra, Niloyen_US
dc.contributor.authorKobbelt, Leifen_US
dc.contributor.editorAlliez, Pierre and Pellacini, Fabioen_US
dc.date.accessioned2019-05-05T17:39:01Z
dc.date.available2019-05-05T17:39:01Z
dc.date.issued2019
dc.description.abstractWe propose a novel method to synthesize geometric models from a given class of context-aware structured shapes such as buildings and other man-made objects. The central idea is to leverage powerful machine learning methods from the area of natural language processing for this task. To this end, we propose a technique that maps shapes to strings and vice versa, through an intermediate shape graph representation. We then convert procedurally generated shape repositories into text databases that, in turn, can be used to train a variational autoencoder. The autoencoder enables higher level shape manipulation and synthesis like, for example, interpolation and sampling via its continuous latent space. We provide project code and pre-trained models.en_US
dc.description.number2
dc.description.sectionheadersProcedural Modeling
dc.description.seriesinformationComputer Graphics Forum
dc.description.volume38
dc.identifier.doi10.1111/cgf.13616
dc.identifier.issn1467-8659
dc.identifier.pages27-36
dc.identifier.urihttps://doi.org/10.1111/cgf.13616
dc.identifier.urihttps://diglib.eg.org:443/handle/10.1111/cgf13616
dc.publisherThe Eurographics Association and John Wiley & Sons Ltd.en_US
dc.subjectI.3.5 [Computer Graphics]
dc.subjectComputational Geometry and Object Modeling
dc.subjectGeometric algorithms
dc.subjectlanguages
dc.subjectand systems
dc.titleString-Based Synthesis of Structured Shapesen_US
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