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dc.contributor.authorHall, P.-
dc.contributor.authorCai, H.-
dc.contributor.authorWu, Q.-
dc.contributor.authorCorradi, T.-
dc.identifier.citationComputational Visual Media, 2015; 1(2):91-103-
dc.description.abstractCross-depiction is the recognition—and synthesis—of objects whether they are photographed, painted, drawn, etc. It is a significant yet underresearched problem. Emulating the remarkable human ability to recognise and depict objects in an astonishingly wide variety of depictive forms is likely to advance both the foundations and the applications of computer vision. In this paper we motivate the cross-depiction problem, explain why it is difficult, and discuss some current approaches. Our main conclusions are (i) appearance-based recognition systems tend to be over-fitted to one depiction, (ii) models that explicitly encode spatial relations between parts are more robust, and (iii) recognition and non-photorealistic synthesis are related tasks.-
dc.description.statementofresponsibilityPeter Hall, Hongping Cai, Qi Wu and Tadeo Corradi-
dc.rights© The Author(s) 2015. This article is published under an open access license. Please check the 'Copyright Information' section for details of this license and what re-use is permitted. If your intended use exceeds what is permitted by the license or if you are unable to locate the licence and re-use information, please contact the Rights and Permissions team.This article is published with open access at
dc.subjectCross-depiction; classification; synthesis; feature; spatial layout; connectivity; representation-
dc.titleCross-depiction problem: recognition and synthesis of photographs and artwork-
dc.typeJournal article-
dc.identifier.orcidWu, Q. [0000-0003-3631-256X]-
Appears in Collections:Aurora harvest 3
Computer Science publications

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