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Pixel-Level Domain Transfer

Donggeun Yoo et al. — ECCV 2016

We present an image-conditional image generation model. The model transfers an input domain to a target domain in semantic level, and generates the target image in pixel level. To generate realistic target images, we employ the real/fake-discriminator in Generative Adversarial Nets, but also introduce a novel domain-discriminator to make the generated image relevant to the input image. We verify our model through a challenging task of generating a piece of clothing from an input image of a dressed person. We present a high quality clothing dataset containing the two domains, and succeed in demonstrating decent results.

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AUTHORS

Donggeun Yoo1, Namil Kim2, Sunggyun Park1 , Anthony Paek1 and In So Kweon2

1Lunit Inc., 2KAIST

PUBLISHED
ECCV 2016

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