1 code implementation • CVPR 2020 • Hyojin Bahng, Sunghyo Chung, Seungjoo Yoo, Jaegul Choo
Despite remarkable success in unpaired image-to-image translation, existing systems still require a large amount of labeled images.
1 code implementation • 9 Jun 2019 • Seungjoo Yoo, Hyojin Bahng, Sunghyo Chung, Junsoo Lee, Jaehyuk Chang, Jaegul Choo
Despite recent advancements in deep learning-based automatic colorization, they are still limited when it comes to few-shot learning.
1 code implementation • CVPR 2019 • Seungjoo Yoo, Hyojin Bahng, Sunghyo Chung, Junsoo Lee, Jaehyuk Chang, Jaegul Choo
Despite recent advancements in deep learning-based automatic colorization, they are still limited when it comes to few-shot learning.
no code implementations • 11 Feb 2019 • Sanghyeon Na, Seungjoo Yoo, Jaegul Choo
First, we use a content representation from the source domain conditioned on a style representation from the target domain.
no code implementations • 7 May 2018 • David Keetae Park, Seungjoo Yoo, Hyojin Bahng, Jaegul Choo, Noseong Park
Recently, generative adversarial networks (GANs) have shown promising performance in generating realistic images.
1 code implementation • ECCV 2018 • Hyojin Bahng, Seungjoo Yoo, Wonwoong Cho, David K. Park, Ziming Wu, Xiaojuan Ma, Jaegul Choo
This paper proposes a novel approach to generate multiple color palettes that reflect the semantics of input text and then colorize a given grayscale image according to the generated color palette.