Papers › Generative Adversarial Networks for photo to Hayao Miyazaki style cartoons
Generative Adversarial Networks for photo to Hayao Miyazaki style cartoons
Filip Andersson, Simon Arvidsson
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.
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