Finding latent representation in other domain about stylegan-encoder HOT 5 CLOSED

Hi @JanBoskamp -- you'd want to use a StyleGAN model that's been trained on portraits, take a look at the notebook in this repo, by @ak9250

For the encoder parameters, you'll need to specify the model_url and the model_res (512 in this case) as well. Here's an example of what you can expect.

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Hi @pbaylies , thanks for your answer, but let me clarify what I mean. With the Stylegan model I have trained, I can create portrait art (similar to @ak9250) and that looks like real art. Very cool. But when I try to find a latent representation in this art domain for an FFHQ image, or an image of myself, the generated image doesn't look like art. Although I am only using the art-stylegan model and not the well-known FFHQ stylegan model to find the representations.

I have attached two example art-stylegan results, and two found latent representations and their images. Any idea how I can force the encoding process to stay more in the art domain? In other words, how can I generate art-stylegan images, with similar facial features as the images of faces I use as input. The example of Elon Musk is the goal I try to achieve with my own model.

Thanks again!

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Oh hey, nice model, I'd love to try that out! What you should try is raising the L1 penalty (the --use_l1_penalty flag), that will pull it more towards the center of the distribution, i.e., the art domain. Try raising it to 2 or 4, probably 20 would be too high, but somewhere in there.

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Looks great, Can you share the pre trained wiki-art network? Also, did you train resnet/effnet on wikiart data?

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@JanBoskamp did you succeed?

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