Please use this identifier to cite or link to this item: https://repository.cihe.edu.hk/jspui/handle/cihe/3544
DC FieldValueLanguage
dc.contributor.authorLi, Chengzeen_US
dc.contributor.authorLiu, Xueting-
dc.contributor.otherLiu, H.-
dc.contributor.otherWong, T.-T.-
dc.date.accessioned2022-10-12T06:43:32Z-
dc.date.available2022-10-12T06:43:32Z-
dc.date.issued2022-
dc.identifier.urihttps://repository.cihe.edu.hk/jspui/handle/cihe/3544-
dc.description.abstractVector graphics is broadly used in a variety of forms, such as illustrations, logos, posters, billboards, and printed ads. Despite its broad use, many artists still prefer to draw with pen and paper, which leads to a high demand of converting raster designs into the vector form. In particular, line drawing is a primary art and attracts many research efforts in automatically converting raster line drawings to vector form. However, the existing methods generally adopt a two-step approach, stroke segmentation and vectorization. Without vector guidance, the raster-based stroke segmentation frequently obtains unsatisfying segmentation results, such as over-grouped strokes and broken strokes. In this paper, we make an attempt in proposing an end-to-end vectorization method which directly generates vectorized stroke primitives from raster line drawing in one step. We propose a Transformer-based framework to perform stroke tracing like human does in an automatic stroke-by-stroke way with a novel stroke feature representation and multi-modal supervision to achieve vectorization with high quality and fidelity. Qualitative and quantitative evaluations show that our method achieves state of the art performance.en_US
dc.language.isoenen_US
dc.publisherAAAI Pressen_US
dc.titleEnd-to-end line drawing vectorizationen_US
dc.typeconference proceedingsen_US
dc.relation.publicationProceedings of the 36th AAAI Conference on Artificial Intelligenceen_US
dc.contributor.affiliationSchool of Computing and Information Sciencesen_US
dc.relation.isbn9781577358763en_US
dc.description.volume36en_US
dc.description.issue4en_US
dc.description.startpage4559en_US
dc.description.endpage4566en_US
dc.cihe.affiliatedYes-
item.fulltextWith Fulltext-
item.grantfulltextopen-
item.cerifentitytypePublications-
item.openairecristypehttp://purl.org/coar/resource_type/c_5794-
item.openairetypeconference proceedings-
item.languageiso639-1en-
crisitem.author.deptSchool of Computing and Information Sciences-
crisitem.author.deptSchool of Computing and Information Sciences-
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