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DTSTART:18871231T000000
DTSTART:19881009T020000
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BEGIN:VEVENT
DTSTAMP:20230103T035307Z
LOCATION:Room 325-AB\, Level 3\, West Wing
DTSTART;TZID=Asia/Seoul:20221206T153000
DTEND;TZID=Asia/Seoul:20221206T170000
UID:siggraphasia_SIGGRAPH Asia 2022_sess157_papers_549@linklings.com
SUMMARY:Dr.3D: Adapting 3D GANs to Artistic Drawings
DESCRIPTION:Technical Communications, Technical Papers\n\nDr.3D: Adapting 
 3D GANs to Artistic Drawings\n\nJin, Ryu, Kim, Baek, Cho\n\nWhile 3D GANs 
 have recently demonstrated the high-quality synthesis of multi-view consis
 tent images and 3D shapes, they are mainly restricted to photo-realistic h
 uman portraits. This paper aims to extend 3D GANs to a different, but mean
 ingful visual form: artistic portrait drawings. However, extending existin
 g 3D GANs to drawings is challenging due to the inevitable geometric ambig
 uity present in drawings. To tackle this, we present Dr.3D, a novel adapta
 tion approach that adapts an existing 3D GAN to artistic drawings. Dr.3D i
 s equipped with three novel components to handle the geometric ambiguity: 
 a deformation-aware 3D synthesis network, an alternating adaptation of pos
 e estimation and image synthesis, and geometric priors. Experiments show t
 hat our approach can successfully adapt 3D GANs to drawings and enable mul
 ti-view consistent semantic editing of drawings.\n\nRegistration Category:
  FULL ACCESS, ON-DEMAND ACCESS\n\nLanguage: ENGLISH\n\nFormat: IN-PERSON, 
 ON-DEMAND
URL:https://sa2022.siggraph.org/en/full-program/?id=papers_549&sess=sess15
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