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TZID:Asia/Tokyo
X-LIC-LOCATION:Asia/Tokyo
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TZOFFSETFROM:+0900
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DTSTART:18871231T000000
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BEGIN:VEVENT
DTSTAMP:20260817T171534Z
LOCATION:Hall B5 (1)\, B Block\, Level 5
DTSTART;TZID=Asia/Tokyo:20241205T111300
DTEND;TZID=Asia/Tokyo:20241205T112700
UID:siggraphasia_SIGGRAPH Asia 2024_sess127_papers_398@linklings.com
SUMMARY:Differentiable Modeling of Material Spreading in Inkjet Printing f
 or Appearance Prediction
DESCRIPTION:Emiliano Luci (Max Planck Institute for Informatics), Fabio Pe
 llacini (Università degli Studi di Modena e Reggio Emilia), and Vahid Baba
 ei (Max Planck Institute for Informatics)\n\nInkjet 3D printers produce so
 lid shapes using very small voxels made of polymeric materials. While stat
 e-of-the-art methods for predicting the appearance of inkjet-printed objec
 ts assume a perfect grid, the printed patterns have an irregular material 
 distribution due to complex spreading behavior. This irregularity leads to
  imprecise appearance predictive tools. Here, we\npropose a fully differen
 tiable method that models the material spreading behavior of inkjet printi
 ng. We use a differentiable simulator along with a differentiable volume r
 enderer. Then, using an image of only one printed calibration pattern, we 
 obtain a generalizable material spreading transformation that can be appli
 ed to an input, nominal grid of materials and produce the effective materi
 al grid. By taking into account the dynamics of the printing process, our 
 method significantly outperforms state of the art 3D printing appearance p
 rediction models.\n\nRegistration Category: Full Access, Full Access Suppo
 rter\n\nLanguage Format: English Language\n\nSession Chair: Lin Lu (Shando
 ng University)\n\n
URL:https://asia.siggraph.org/2024/program/?id=papers_398&sess=sess127
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