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Deep graphics encoder for real-time video makeup synthesis from example

  • Robin Kips
  • , Ruowei Jiang
  • , Sileye Ba
  • , Edmund Phung
  • , Parham Aarabi
  • , Pietro Gori
  • , Matthieu Perrot
  • , Isabelle Bloch

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

While makeup virtual-try-on is now widespread, parametrizing a computer graphics rendering engine for synthesizing images of a given cosmetics product remains a challenging task. In this paper, we introduce an inverse computer graphics method for automatic makeup synthesis from a reference image, by learning a model that maps an example portrait image with makeup to the space of rendering parameters. This method can be used by artists to automatically create realistic virtual cosmetics image samples, or by consumers, to virtually try-on a makeup extracted from their favorite reference image.

Original languageEnglish
Title of host publicationProceedings - 2021 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, CVPRW 2021
PublisherIEEE Computer Society
Pages3884-3888
Number of pages5
ISBN (Electronic)9781665448994
DOIs
Publication statusPublished - 1 Jun 2021
Event2021 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, CVPRW 2021 - Virtual, Online, United States
Duration: 19 Jun 202125 Jun 2021

Publication series

NameIEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops
ISSN (Print)2160-7508
ISSN (Electronic)2160-7516

Conference

Conference2021 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, CVPRW 2021
Country/TerritoryUnited States
CityVirtual, Online
Period19/06/2125/06/21

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