BEGIN:VCALENDAR
VERSION:2.0
PRODID:Linklings LLC
BEGIN:VTIMEZONE
TZID:Australia/Melbourne
X-LIC-LOCATION:Australia/Melbourne
BEGIN:DAYLIGHT
TZOFFSETFROM:+1000
TZOFFSETTO:+1100
TZNAME:AEDT
DTSTART:19721003T020000
RRULE:FREQ=YEARLY;BYMONTH=4;BYDAY=1SU
END:DAYLIGHT
BEGIN:STANDARD
DTSTART:19721003T020000
TZOFFSETFROM:+1100
TZOFFSETTO:+1000
TZNAME:AEST
RRULE:FREQ=YEARLY;BYMONTH=10;BYDAY=1SU
END:STANDARD
END:VTIMEZONE
BEGIN:VEVENT
DTSTAMP:20260114T163657Z
LOCATION:Meeting Room C4.9+C4.10\, Level 4 (Convention Centre)
DTSTART;TZID=Australia/Melbourne:20231214T114000
DTEND;TZID=Australia/Melbourne:20231214T115000
UID:siggraphasia_SIGGRAPH Asia 2023_sess170_papers_473@linklings.com
SUMMARY:Diffusing Colors: Image Colorization with Text Guided Diffusion
DESCRIPTION:Nir Zabari, Aharon Azulay, Alexey Gorkor, and Tavi Halperin (L
 ightricks) and Ohad Fried (Reichman University)\n\nThe colorization of gra
 yscale images is a complex and subjective task with significant challenges
 . Despite recent progress in employing large-scale datasets with deep neur
 al networks, difficulties with controllability and visual quality persist.
  To tackle these issues, we present a novel image colorization framework t
 hat utilizes image diffusion techniques with granular text prompts.\nThis 
 integration not only produces colorization outputs that are semantically a
 ppropriate but also greatly improves the level of control users have over 
 the colorization process. Our method provides a balance between automation
  and control, outperforming existing techniques in terms of visual quality
  and semantic coherence. We leverage a pretrained generative Diffusion Mod
 el, and show that we can finetune it for the colorization task without los
 ing its generative power or attention to text prompts.  \nMoreover, we pre
 sent a novel CLIP-based ranking model that evaluates color vividness, enab
 ling automatic selection of the most suitable level of vividness based on 
 the specific scene semantics. Our approach holds potential particularly fo
 r color enhancement and historical image colorization.\n\nRegistration Cat
 egory: Full Access\n\nSession Chair: Xiangyu Xu (Xi'an Jiaotong University
 )\n\n
URL:https://asia.siggraph.org/2023/full-program?id=papers_473&sess=sess170
END:VEVENT
END:VCALENDAR