Historical context & research account
CycleGAN uses cycle consistency to learn translation between unpaired image domains, extending tasks such as changes of season, transformations between painting and photographic domains, and changes in object appearance. It helps develop the idea that a visual domain or style can be learned statistically and transformed into another.
Dates & version record
Date displayed for this node：2017 · Date recorded in the research master：2017
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Original sources & further reading
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CycleGAN
https://openaccess.thecvf.com/content_iccv_2017/html/Zhu_Unpaired_Image-To-Image_Translation_ICCV_2017_paper.html
Current cited URL
Provenance, translation & verification
Archive node #057 · Historical node
Research masters & supplement references · 1
AI Art Genealogy Research Master · p. 18 · 057
Date as recorded: 2017
CycleGAN ↗
CycleGAN
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Cite this node
ANTI-AI ARCHIVE. CycleGAN. Art-history node #057. https://salondesrefuses.cn/en/art-history/057
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