Two‐Step Training: Adjustable Sketch Colourization via Reference Image and Text Tag

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dc.contributor.authorYan, Dingkunen_US
dc.contributor.authorIto, Ryogoen_US
dc.contributor.authorMoriai, Ryoen_US
dc.contributor.authorSaito, Suguruen_US
dc.contributor.editorHauser, Helwig and Alliez, Pierreen_US
dc.date.accessioned2023-10-06T11:58:53Z
dc.date.available2023-10-06T11:58:53Z
dc.date.issued2023
dc.description.abstractAutomatic sketch colourization is a highly interestinged topic in the image‐generation field. However, due to the absence of texture in sketch images and the lack of training data, existing reference‐based methods are ineffective in generating visually pleasant results and cannot edit the colours using text tags. Thus, this paper presents a conditional generative adversarial network (cGAN)‐based architecture with a pre‐trained convolutional neural network (CNN), reference‐based channel‐wise attention (RBCA) and self‐adaptive multi‐layer perceptron (MLP) to tackle this problem. We propose two‐step training and spatial latent manipulation to achieve high‐quality and colour‐adjustable results using reference images and text tags. The superiority of our approach in reference‐based colourization is demonstrated through qualitative/quantitative comparisons and user studies with existing network‐based methods. We also validate the controllability of the proposed model and discuss the details of our latent manipulation on the basis of experimental results of multi‐label manipulation.en_US
dc.description.number6
dc.description.sectionheadersORIGINAL ARTICLES
dc.description.seriesinformationComputer Graphics Forum
dc.description.volume42
dc.identifier.doi10.1111/cgf.14791
dc.identifier.issn1467-8659
dc.identifier.urihttps://doi.org/10.1111/cgf.14791
dc.identifier.urihttps://diglib.eg.org:443/handle/10.1111/cgf14791
dc.publisher© 2023 Eurographics ‐ The European Association for Computer Graphics and John Wiley & Sons Ltd.en_US
dc.rightsAttribution 4.0 International License
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/
dc.subjectcolour
dc.subjectimage and video processing
dc.subjectimage/video editing
dc.titleTwo‐Step Training: Adjustable Sketch Colourization via Reference Image and Text Tagen_US
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