Learning to Shadow Hand-Drawn Sketches

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dc.contributor.authorZheng, Qingyuan
dc.contributor.authorLi, Zhuoru
dc.contributor.authorBargteil, Adam
dc.date.accessioned2020-10-20T18:56:35Z
dc.date.available2020-10-20T18:56:35Z
dc.date.issued2020-08-05
dc.description2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)en_US
dc.description.abstractWe present a fully automatic method to generate detailed and accurate artistic shadows from pairs of line drawing sketches and lighting directions. We also contribute a new dataset of one thousand examples of pairs of line drawings and shadows that are tagged with lighting directions. Remarkably, the generated shadows quickly communicate the underlying 3D structure of the sketched scene. Consequently, the shadows generated by our approach can be used directly or as an excellent starting point for artists. We demonstrate that the deep learning network we propose takes a hand-drawn sketch, builds a 3D model in latent space, and renders the resulting shadows. The generated shadows respect the hand-drawn lines and underlying 3D space and contain sophisticated and accurate details, such as self-shadowing effects. Moreover, the generated shadows contain artistic effects, such as rim lighting or halos appearing from backlighting, that would be achievable with traditional 3D rendering methods.en_US
dc.description.urihttps://ieeexplore.ieee.org/document/9156735en_US
dc.format.extent10 pagesen_US
dc.genreconference papers and proceedings preprintsen_US
dc.identifierdoi:10.13016/m2j5b1-idyz
dc.identifier.citationZheng, Qingyuan; Li, Zhuoru; Bargteil, Adam; Learning to Shadow Hand-Drawn Sketches; 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR); https://ieeexplore.ieee.org/document/9156735en_US
dc.identifier.urihttps://doi.org/10.1109/CVPR42600.2020.00746
dc.identifier.urihttp://hdl.handle.net/11603/19939
dc.language.isoen_USen_US
dc.publisherIEEEen_US
dc.relation.isAvailableAtThe University of Maryland, Baltimore County (UMBC)
dc.relation.ispartofUMBC Computer Science and Electrical Engineering Department Collection
dc.relation.ispartofUMBC Faculty Collection
dc.rightsThis item is likely protected under Title 17 of the U.S. Copyright Law. Unless on a Creative Commons license, for uses protected by Copyright Law, contact the copyright holder or the author.
dc.titleLearning to Shadow Hand-Drawn Sketchesen_US
dc.typeTexten_US

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