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 as 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.
Publications
International Conference
Pixel-Level Domain Transfer
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저 자 | Donggeun Yoo, Namil Kim, Sunggyun Park, Anthony S. Paek, In So Kweon |
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학 회 | European Conference on Computer Vision (ECCV) |
논문일시(Year) | 2016 |
논문일시(Month) | 10 |