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DTSTAMP:20240214T070250Z
LOCATION:Meeting Room C4.8\, Level 4 (Convention Centre)
DTSTART;TZID=Australia/Melbourne:20231215T135500
DTEND;TZID=Australia/Melbourne:20231215T141000
UID:siggraphasia_SIGGRAPH Asia 2023_sess157_papers_441@linklings.com
SUMMARY:Reconstruction of Machine-Made Shapes from Bitmap Sketches
DESCRIPTION:Technical Papers, TOG\n\nIvan Puhachov (Universite de Montreal
 ; Huawei Technologies, Canada); Cedric Martens (Universite de Montreal); P
 aul G. Kry (McGill University; Huawei Technologies, Canada); and Mikhail B
 essmeltsev (Universite de Montreal)\n\nWe propose a method of reconstructi
 ng 3D machine-made shapes from bitmap sketches by separating an input imag
 e into individual patches and jointly optimizing their geometry. \nWe rely
  on two main observations:\n(1) human observers interpret sketches of man-
 made shapes as a collection of simple geometric primitives, and \n(2) sket
 ch strokes often indicate occlusion contours or sharp ridges between those
  primitives.\nUsing these main observations we design a system that takes 
 a single bitmap image of a shape, estimates image depth and segmentation i
 nto primitives with neural networks, then fits primitives into the predict
 ed depth while determining occlusion contours and aligning intersections w
 ith input drawing via optimization.\nUnlike previous work, our approach do
 es not require additional input, annotation, or templates, and does not re
 quire retraining for a new category of man-made shapes. \nOur method produ
 ces triangular meshes that display sharp geometric features and are suitab
 le for downstream applications, such as editing, rendering, and shading.\n
 \nRegistration Category: Full Access\n\nSession Chair: Chi Wing Fu (The Ch
 inese University of Hong Kong)
URL:https://asia.siggraph.org/2023/full-program?id=papers_441&sess=sess157
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