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dc.contributor.authorAkita, Kentaen_US
dc.contributor.authorMorimoto, Yukien_US
dc.contributor.authorTsuruno, Reijien_US
dc.contributor.editorEisemann, Elmar and Jacobson, Alec and Zhang, Fang-Lueen_US
dc.date.accessioned2020-10-29T18:51:21Z
dc.date.available2020-10-29T18:51:21Z
dc.date.issued2020
dc.identifier.issn1467-8659
dc.identifier.urihttps://doi.org/10.1111/cgf.14171
dc.identifier.urihttps://diglib.eg.org:443/handle/10.1111/cgf14171
dc.description.abstractMany studies have recently applied deep learning to the automatic colorization of line drawings. However, it is difficult to paint empty pupils using existing methods because the convolutional neural network are trained with pupils that have edges, which are generated from color images using image processing. Most actual line drawings have empty pupils that artists must paint in. In this paper, we propose a novel network model that transfers the pupil details in a reference color image to input line drawings with empty pupils. We also propose a method for accurately and automatically colorizing eyes. In this method, eye patches are extracted from a reference color image and automatically added to an input line drawing as color hints using our pupil position estimation network.en_US
dc.publisherThe Eurographics Association and John Wiley & Sons Ltd.en_US
dc.subjectComputing methodologies
dc.subjectImage processing
dc.subjectApplied computing
dc.subjectFine arts
dc.titleColorization of Line Drawings with Empty Pupilsen_US
dc.description.seriesinformationComputer Graphics Forum
dc.description.sectionheadersStylized Graphics
dc.description.volume39
dc.description.number7
dc.identifier.doi10.1111/cgf.14171
dc.identifier.pages601-610


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  • 39-Issue 7
    Pacific Graphics 2020 - Symposium Proceedings

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