//=time() ?>
Today's reverse toonification experiments with art from @Pixar for Incredibles 2, Up, & Coco.
This framework from @EladRichardson and @yuvalalaluf quickly finds a "real" human face in the #StyleGAN FFHQ latent space. Adding some style randomness too.
More Pixar in thread! ⬇️
(1) Alex, (2) Agaricalic Horror, (3) Apprehension, and (4) Aqueous, Not Acquiescent from my adversarial AI art series "Artifice & Insight" are now available on @NftShowroom.
Evocative portraits born of StyleGAN conjuring faces whence there were none.
50 - 300 swap.hive each.
After many, many months, @AydaoGMan 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.
Taking layer swapping further: Resolution dependant interpolation between StyleGAN models lets you transplant My Little Pony eyes into anime faces. https://t.co/6iNX3Oxmqv
My #PranksyLand 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 @pranksyNFT my friend for this opportunity.
@cryptovoxels
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
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.
https://t.co/0LLvkfWRoN #deepdreamgenerator #ddgart #digitalart #styletransfer #neuralstyle #styleGAN @pexels @DeepDreamGen #neuralnetworks #transfer #ArtificialIntelligence #daily #everyday #wineglass original photo by Alina Vilchenko
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
@scarfofsilver 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!
#StyleGAN2 pokemon sprites after being fed through https://t.co/QPHaoyZ90b