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DTSTART:18871231T000000
DTSTART:19881009T020000
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BEGIN:VEVENT
DTSTAMP:20230103T035306Z
LOCATION:Auditorium\, Level 5\, West Wing
DTSTART;TZID=Asia/Seoul:20221206T100000
DTEND;TZID=Asia/Seoul:20221206T120000
UID:siggraphasia_SIGGRAPH Asia 2022_sess153_papers_549@linklings.com
SUMMARY:Dr.3D: Adapting 3D GANs to Artistic Drawings
DESCRIPTION:Technical Papers\n\nDr.3D: Adapting 3D GANs to Artistic Drawin
 gs\n\nJin, Ryu, Kim, Baek, Cho\n\nWhile 3D GANs have recently demonstrated
  the high-quality synthesis of multi-view consistent images and 3D shapes,
  they are mainly restricted to photo-realistic human portraits. This paper
  aims to extend 3D GANs to a different, but meaningful visual form: artist
 ic portrait drawings. However, extending existing 3D GANs to drawings is c
 hallenging due to the inevitable geometric ambiguity present in drawings. 
 To tackle this, we present Dr.3D, a novel adaptation approach that adapts 
 an existing 3D GAN to artistic drawings. Dr.3D is equipped with three nove
 l components to handle the geometric ambiguity: a deformation-aware 3D syn
 thesis network, an alternating adaptation of pose estimation and image syn
 thesis, and geometric priors. Experiments show that our approach can succe
 ssfully adapt 3D GANs to drawings and enable multi-view consistent semanti
 c editing of drawings.\n\nRegistration Category: FULL ACCESS, EXPERIENCE P
 LUS ACCESS, EXPERIENCE ACCESS, TRADE EXHIBITOR\n\nLanguage: ENGLISH\n\nFor
 mat: IN-PERSON
URL:https://sa2022.siggraph.org/en/full-program/?id=papers_549&sess=sess15
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