Hi everyone. I’ve been working on a project where I use StyleGAN to generate fake images of characters from Game of Thrones. I wrote an article that describes that algorithms and methods used, and you can try it out yourself via a Colab notebook.

Game of Thrones character animations from StyleGAN

Here are the resources to follow along:

• Article: https://blog.nanonets.com/stylegan-got/
• Colab notebook: https://colab.research.google.com/github/iyaja/stylegan-encoder/blob/master/generate_GoT_characters_with_StyleGAN.ipynb
• GitHub repo: https://github.com/iyaja/stylegan-encoder

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Something interesting to note: All the results (images and animations) were generated from Nvidia’s StyleGAN that was pretrained on the FFHQ dataset, with absolutely no fine-tuning.

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Instead, to make StyleGAN work for Game of Thrones characters, I used another model (credit to this GitHub repo) that maps images onto StyleGAN’s latent space. I gave it images of Jon, Daenerys, Jaime, etc. and got latent vectors that when fed through StyleGAN, recreate the original image.

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With the latent vectors for the images in hand, it’s really to modify them in all the ways described in the StyleGAN paper (style mixing, interpolations, etc.) as well as through simple arithmetic in the latent space (such as shifting the latent vector in the “smiling direction”). As a bonus, since there’s no StyleGAN training involved, all the steps that I just mentioned can be executed extremely fast.

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Also, stick around to the end of the article to see a result of character style mixing that might be very interesting to Game of Thrones fans.