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dc.contributor.authorAkita, Kentaen_US
dc.contributor.authorMorimoto, Yukien_US
dc.contributor.authorTsuruno, Reijien_US
dc.contributor.editorWilkie, Alexander and Banterle, Francescoen_US
dc.date.accessioned2020-05-24T13:43:14Z
dc.date.available2020-05-24T13:43:14Z
dc.date.issued2020
dc.identifier.isbn978-3-03868-101-4
dc.identifier.issn1017-4656
dc.identifier.urihttps://doi.org/10.2312/egs.20201023
dc.identifier.urihttps://diglib.eg.org:443/handle/10.2312/egs20201023
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 networks 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 coloring 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 eye position estimation network.en_US
dc.publisherThe Eurographics Associationen_US
dc.rightsAttribution 4.0 International License
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/]
dc.subjectComputing methodologies
dc.subjectImage processing
dc.subjectApplied computing
dc.subjectFine arts
dc.titleDeep-Eyes: Fully Automatic Anime Character Colorization with Painting of Details on Empty Pupilsen_US
dc.description.seriesinformationEurographics 2020 - Short Papers
dc.description.sectionheadersVisualisation / NPR
dc.identifier.doi10.2312/egs.20201023
dc.identifier.pages81-84


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Attribution 4.0 International License
Except where otherwise noted, this item's license is described as Attribution 4.0 International License