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DTSTAMP:20260817T171531Z
LOCATION:Hall B7 (1)\, B Block\, Level 7
DTSTART;TZID=Asia/Tokyo:20241205T151900
DTEND;TZID=Asia/Tokyo:20241205T153100
UID:siggraphasia_SIGGRAPH Asia 2024_sess135_papers_335@linklings.com
SUMMARY:DrawingSpinUp: 3D Animation from Single Character Drawings
DESCRIPTION:Jie ZHOU (City University of Hong Kong), Chufeng XIAO (Hong Ko
 ng University of Science and Technology), Miu-Ling LAM (City University of
  Hong Kong), and Hongbo FU (Hong Kong University of Science and Technology
 )\n\nAnimating various character drawings is an engaging visual content cr
 eation task. Given a single character drawing, existing animation methods 
 are limited to flat 2D motions and thus lack 3D effects. An alternative so
 lution is to reconstruct a 3D model from a character drawing as a proxy an
 d then retarget 3D motion data onto it. However, the existing image-to-3D 
 methods could not work well for amateur character drawings in terms of app
 earance and geometry. We observe the contour lines, commonly existing in c
 haracter drawings, would introduce significant ambiguity in texture synthe
 sis due to their view-dependence. Additionally, thin regions represented b
 y single-line contours are difficult to reconstruct (e.g., slim limbs of a
  stick figure) due to their delicate structures. To address these issues, 
 we propose a novel system, DrawingSpinUp, to produce plausible 3D animatio
 ns and breathe life into character drawings, allowing them to freely spin 
 up, leap, and even perform a hip-hop dance. For appearance improvement, we
  adopt a removal-then-restoration strategy to first remove the view-depend
 ent contour lines and then render them back after retargeting the reconstr
 ucted character. For geometry refinement, we develop a skeleton-based thin
 ning deformation algorithm to refine the slim structures represented by th
 e single-line contours. The experimental evaluations show that our propose
 d method outperforms the existing 2D and 3D animation methods and generate
 s high-quality 3D animations from a single character drawing.\n\nRegistrat
 ion Category: Full Access, Full Access Supporter\n\nLanguage Format: Engli
 sh Language\n\nSession Chair: Changjian Li (University of Edinburgh)\n\n
URL:https://asia.siggraph.org/2024/program/?id=papers_335&sess=sess135
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