This paper takes on the problem of transferring the style of cartoon images to real-life photographic images by implementing previous work done by CartoonGAN. We trained a Generative Adversial Network(GAN) on over 60 000 images from works by Hayao Miyazaki at Studio Ghibli. To evaluate our results, we conducted a qualitative survey comparing our results with two state-of-the-art methods. 117 survey results indicated that our model on average outranked state-of-the-art methods on cartoon-likeness.
翻译:本文探讨了通过实施卡通GAN以前的工作将卡通图像的风格转换为真实摄影图像的问题。我们培训了一个创举反响网络,对工作室Ghibli的Hayao Miyazaki作品的6万多张图像进行了培训。为了评估我们的结果,我们进行了定性调查,将我们的结果与两种最先进的方法进行了比较。 117项调查结果表明,我们在卡通相似性方面的平均领先于最先进的方法模式。