StarGAN: Unified Generative Adversarial Networks for Multi-domain Image-to-Image Translation

Recent studies have shown remarkable success in image-to-image translation for two domains. However, existing approaches have limited scalability and robustness in handling more than two domains, since different models should be built independently for every pair of image domains. To address this li...

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Vydané v:	2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition s. 8789 - 8797
Hlavní autori:	Choi, Yunjey, Choi, Minje, Kim, Munyoung, Ha, Jung-Woo, Kim, Sunghun, Choo, Jaegul
Médium:	Konferenčný príspevok..
Jazyk:	English
Vydavateľské údaje:	IEEE 01.06.2018
Predmet:	Gallium nitride Generative adversarial networks Generators Hair Image reconstruction Task analysis Training
ISSN:	1063-6919
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