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Dec, 2019
StarGAN v2：多领域多样化图像合成
StarGAN v2: Diverse Image Synthesis for Multiple Domains
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Yunjey Choi, Youngjung Uh, Jaejun Yoo, Jung-Woo Ha
TL;DR
提出了单个框架StarGAN v2，用于解决图像到图像翻译模型中的多种领域转换问题，并在CelebA-HQ和新的动物面孔数据集（AFHQ）上进行了实验证明了其在视觉质量，多样性和可伸缩性方面的优越性。
Abstract
A good
image-to-image translation
model should learn a mapping between different
visual domains
while satisfying the following properties: 1) diversity of generated images and 2) scalability over multiple domains
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