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BEGIN:VEVENT
DTSTAMP:20260805T205607Z
LOCATION:Room 408 B
DTSTART;TZID=America/Los_Angeles:20260722T091000
DTEND;TZID=America/Los_Angeles:20260722T092000
UID:siggraph_SIGGRAPH 2026_sess154_papers_1680@linklings.com
SUMMARY:BFS: Back-to-Front Layered Image Synthesis via Knowledge Transfer
DESCRIPTION:Kyoungkook Kang (Samsung) and Gyujin Sim and Sunghyun Cho (POS
 TECH)\n\nBFS is a novel generation-based framework for layered image synth
 esis that produces foreground layers with realistic visual effects while h
 armonizing with a given background. Using a dual-branch diffusion model an
 d two-stage training with unlayered data, it overcomes data scarcity and a
 chieves superior quality and diversity compared to prior methods.\n\nInter
 est Area: Research & Education\n\nKeyword: Artificial Intelligence/Machine
  Learning, Generative AI, Modeling\n\nRegistration Category: Full Conferen
 ce Supporter, Full Conference\n\nSession Chair: Justin Solomon (Massachuse
 tts Institute of Technology (MIT))\n\n
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