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X-LIC-LOCATION:Asia/Seoul
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DTSTART:18871231T000000
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DTSTAMP:20230103T035307Z
LOCATION:Auditorium\, Level 5\, West Wing
DTSTART;TZID=Asia/Seoul:20221206T100000
DTEND;TZID=Asia/Seoul:20221206T120000
UID:siggraphasia_SIGGRAPH Asia 2022_sess153_papers_588@linklings.com
SUMMARY:Neural Photo-Finishing
DESCRIPTION:Technical Papers\n\nNeural Photo-Finishing\n\nTseng, Zhang, Je
 be, Zhang, Xia...\n\nImage processing pipelines are ubiquitous and we rely
  on them either directly, by filtering or adjusting an image post-capture,
  or indirectly, as image signal processing pipeline (ISP) on broadly deplo
 yed camera systems. Used by artists, photographers, system engineers, and 
 for downstream vision tasks, traditional image processing pipelines featur
 e complex algorithmic branches developed over decades. Recently, image-to-
 image networks have made great strides in image processing, style transfer
 , and semantic understanding. The differentiable nature of these networks 
 allows them to fit a large corpus of data, however, they do not allow for 
 intuitive, fine-grained controls that photographers find in modern photo-f
 inishing tools.\n\nThis work closes this gap and presents an approach to m
 aking complex photo-finishing pipelines differentiable, allowing legacy al
 gorithms to be trained akin to neural networks using first-order optimizat
 ion methods. By concatenating tailored network proxy models of individual 
 processing steps (e.g. white-balance, tone-mapping, color tuning), we can 
 model a non-differentiable reference image finishing pipeline more faithfu
 lly than existing proxy image-to-image network models. We validate the met
 hod for several diverse applications, including photo and video style tran
 sfer, slider regression for commercial camera ISPs, photography-driven neu
 ral demosaicking, and adversarial photo-editing.\n\nRegistration Category:
  FULL ACCESS, EXPERIENCE PLUS ACCESS, EXPERIENCE ACCESS, TRADE EXHIBITOR\n
 \nLanguage: ENGLISH\n\nFormat: IN-PERSON
URL:https://sa2022.siggraph.org/en/full-program/?id=papers_588&sess=sess15
 3
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