Image-to-Image Translation with Conditional Adversarial Networks

We investigate conditional adversarial networks as a general-purpose solution to image-to-image translation problems. These networks not only learn the mapping from input image to output image, but also learn a loss function to train this mapping. This makes it possible to apply the same generic app...

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Vydané v:	2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR) s. 5967 - 5976
Hlavní autori:	Isola, Phillip, Jun-Yan Zhu, Tinghui Zhou, Efros, Alexei A.
Médium:	Konferenčný príspevok..
Jazyk:	English
Vydavateľské údaje:	IEEE 01.07.2017
Predmet:	Force Gallium nitride Generators Image edge detection Image resolution Training
ISSN:	1063-6919, 1063-6919
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