画質 高画質

. showed what your favorite characters from Pixar films would look like with the help of StyleGAN and Pixel2Style2Pixel:

https://t.co/YkJsujoAyt

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Today's reverse toonification experiments with art from for Incredibles 2, Up, & Coco.

This framework from and quickly finds a "real" human face in the FFHQ latent space. Adding some style randomness too.

More Pixar in thread! ⬇️

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stylegan2-ada anime n=1k finetuning

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stylegan2 cartoonset is now on runwayml
link: https://t.co/z12PR034qy

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(1) Alex, (2) Agaricalic Horror, (3) Apprehension, and (4) Aqueous, Not Acquiescent from my adversarial AI art series "Artifice & Insight" are now available on .

Evocative portraits born of StyleGAN conjuring faces whence there were none.

50 - 300 swap.hive each.

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After many, many months, has finally cracked “stylegan on complex datasets”. Look how good these are! Trained on 2M danbooru photos, I think.

I can’t overstate how much work this took. There are so many variants to try that I basically gave up.

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Taking layer swapping further: Resolution dependant interpolation between StyleGAN models lets you transplant My Little Pony eyes into anime faces. https://t.co/6iNX3Oxmqv

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My build is a podium with 7 of my artworks showcased. These were AI generated (StyleGAN) from a custom water-colour dataset that I curated. Do read about the full project at:
https://t.co/PMlb8TC4SO
Thanks my friend for this opportunity.

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what i've been messing with most recently: creating 3D texture maps out of the 'GANime girl' (my own name for them) images generated from gwern's "this waifu does not exist" styleGAN

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人工知能が作ったキャラ
私はこれの少女漫画ヒロイン版を作りたいけど、styleganのやり方が分からずに断念

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After all, StyleGAN's architecture is quite similar to BigGAN. So it must be due to one of the "bells and whistles" that StyleGAN comes with.

I'll just give the answer: Style mixing on (left, step 26k), style mixing off (right, 24k). Note how much more cohesive the bodies are.

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Following up, another interpolation video of the same model much later in training. It really seems that, despite this one being trained on random cropping, StyleGAN2 prefers generating centrally-placed objects (especially evident in comparison with BigGAN...) https://t.co/XQwTEb7NbY

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I always love applications of the styleGAN projects like this!

I was actually trying to train something exactly like this for a while but labored the compute power and py understanding

It can for sure make some cool sona's though and I hope those rp accounts move to these now!

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