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BEGIN:VEVENT
DTSTAMP:20250522T212946Z
LOCATION:Mile High 1
DTSTART;TZID=America/Denver:20240801T091000
DTEND;TZID=America/Denver:20240801T092000
UID:siggraph_SIGGRAPH 2024_sess142_papers_901@linklings.com
SUMMARY:Filter-Guided Diffusion for Controllable Image Generation
DESCRIPTION:Zeqi Gu (Cornell-Tech Cornell University) and Ethan Yang and A
 be Davis (Cornell University)\n\nFilter-Guided Diffusion (FGD) is a contro
 llable, tuning-free, image-to-image translation method for diffusion model
 s. It combines fast filtering operations with non-deterministic samplers t
 o generate high-quality and diverse images. With its efficiency, FGD can b
 e sampled multiple times to outperform previous methods in less time on st
 ructural and semantic metrics.\n\nInterest Area: Research & Education\n\nR
 ecording: Livestreamed, Recorded\n\nRegistration Category: Full Conference
 , Full Conference Supporter, Virtual Access, Exhibitor Full Conference, Th
 ursday\n\nSession Chair: Cecilia Zhang (Adobe, University of California Be
 rkeley)\n\n
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