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DTSTAMP:20240214T070244Z
LOCATION:Meeting Room C4.11\, Level 4 (Convention Centre)
DTSTART;TZID=Australia/Melbourne:20231213T130000
DTEND;TZID=Australia/Melbourne:20231213T131500
UID:siggraphasia_SIGGRAPH Asia 2023_sess169_papers_220@linklings.com
SUMMARY:Towards Garment Sewing Pattern Reconstruction from a Single Image
DESCRIPTION:Technical Communications, Technical Papers, TOG\n\nLijuan Liu 
 (Sea AI Lab); Xiangyu Xu (Xi'an Jiaotong University, Sea AI Lab); and Zhij
 ie Lin, Jiabin Liang, and Shuicheng Yan (Sea AI Lab)\n\nGarment sewing pat
 tern represents the intrinsic rest shape of a garment, and is the core for
  many applications like fashion design, virtual try-on, and digital avatar
 s. In this work, we explore the challenging problem of recovering garment 
 sewing patterns from daily photos for augmenting these applications. To so
 lve the problem, we first synthesize a versatile dataset, named SewFactory
 , which consists of around 1M images and ground-truth sewing patterns for 
 model training and quantitative evaluation. SewFactory covers a wide range
  of human poses, body shapes, and sewing patterns, and possesses realistic
  appearances thanks to the proposed human texture synthesis network. Then,
  we propose a two-level Transformer network called Sewformer, which signif
 icantly improves the sewing pattern prediction performance. Extensive expe
 riments demonstrate that the proposed framework is effective in recovering
  sewing patterns and well generalizes to casually-taken human photos.\n\nR
 egistration Category: Full Access\n\nSession Chair: Bernd Bickel (Institut
 e of Science and Technology Austria, Google)
URL:https://asia.siggraph.org/2023/full-program?id=papers_220&sess=sess169
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