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DTSTAMP:20260817T171536Z
LOCATION:Hall B5 (1)\, B Block\, Level 5
DTSTART;TZID=Asia/Tokyo:20241204T144500
DTEND;TZID=Asia/Tokyo:20241204T155500
UID:siggraphasia_SIGGRAPH Asia 2024_sess118@linklings.com
SUMMARY:Threads of Reality: Garments & Knitting
DESCRIPTION:Each Paper gives a 10 minute presentation.\n\nGarVerseLOD: Hig
 h-Fidelity 3D Garment Reconstruction from a Single In-the-Wild Image using
  a Dataset with Levels of Details\n\nNeural implicit functions have brough
 t impressive advances to the state-of-the-art of clothed human digitizatio
 n from multiple or even single images. However, despite the progress, curr
 ent arts still have difficulty generalizing to unseen images with complex 
 cloth deformation and body poses. In this...\n\n\nZhongjin Luo, Haolin Liu
 , Chenghong Li, Wanghao Du, Zirong Jin, and Wanhu Sun (Chinese University 
 of Hong Kong, Shenzhen); Yinyu Nie (Huawei Technologies Ltd.); Weikai Chen
  (Tencent America); and Xiaoguang Han (Chinese University of Hong Kong, Sh
 enzhen)\n---------------------\nFabricDiffusion: High-Fidelity Texture Tra
 nsfer for 3D Garments Generation from In-The-Wild Images\n\nWe introduce F
 abricDiffusion, a method for transferring fabric textures from a single cl
 othing image to 3D garments of arbitrary shapes. Existing approaches typic
 ally synthesize textures on the garment surface through 2D-to-3D texture m
 apping or depth-aware inpainting via generative models. Unfortun...\n\n\nC
 heng Zhang (Carnegie Mellon University, Texas A&M University); Yuanhao Wan
 g and Francisco Vicente (Carnegie Mellon University); Chenglei Wu, Jinlong
  Yang, and Thabo Beeler (Google Inc.); and Fernando De la Torre (Carnegie 
 Mellon University)\n---------------------\nChebyshev Parameterization for 
 Woven Fabric Modeling\n\nDistortion-minimizing surface parameterization is
  an essential step for computing 2D pieces necessary to fabricate a target
  3D shape from flat material. Garment design and textile fabrication are a
  prominent application example. Common distortion measures quantify length
 , angle or area preservation ...\n\n\nAnnika Oehri (ETH Zürich) and Aviv S
 egall, Jing Ren, and Olga Sorkine-Hornung (ETH Zurich)\n------------------
 ---\nUFO Instruction Graphs Are Machine Knittable\n\nProgramming low-level
  controls for knitting machines is a meticulous, time-consuming task that 
 demands specialized expertise. Recently, there has been a shift towards au
 tomatically generating low-level knitting machine programs from high-level
  knit representations that describe knit objects in a mor...\n\n\nJenny Li
 n (Carnegie Mellon University), Yuka Ikarashi (Massachusetts Institute of 
 Technology), Gilbert Bernstein (University of Washington), and James McCan
 n (Carnegie Mellon University)\n---------------------\nVolumetric Homogeni
 zation for Knitwear Simulation\n\nWe present volumetric homogenization,  a
  spatially varying homogenization scheme for knitwear simulation. We are m
 otivated by the observation that macro-scale fabric dynamics is strongly c
 orrelated with its underlying knitting patterns. Therefore, homogenization
  towards a single\nmaterial is less eff...\n\n\nChun Yuan, Haoyang Shi, an
 d Lei Lan (University of Utah); Yuxing Qiu (LightSpeed Studios); Cem Yukse
 l (University of Utah); Huamin Wang (Style3D Research); Chenfanfu Jiang (U
 niversity of California Los Angeles); Kui Wu (LightSpeed Studios); and Yin
  Yang (University of Utah)\n\nRegistration Category: Full Access, Full Acc
 ess Supporter\n\nLanguage Format: English Language\n\nSession Chair: Meng 
 Zhang (Nanjing University of Science and Technology)
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