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AIによる自動生成(StyleGAN2を活用したとのこと)
顔だけじゃなくて、体も生成されてて凄い。なかには漫画っぽいのも生成されてて、言葉らしきものまで生成されているが、言語は解読不能
https://t.co/sTU6rSDVvv
-- this anime isn't real --
(teaser for the stylegan2 model that is to be released soon™ ... keep an eye on @gwern @arfafax and @theshawwn)
機械学習させたFurryの画像のlatent space walkです。ぶっちゃけ怖い。そんで750%のUpresしてます(もとは256x256px --> 1536x1536px)So I returned to my AI furry StyleGan2. It's friggin scary. I then used AI to upres the whole thing from 256px to 1536px. Not bad!
The last day of ghosts ? This my last one :) #mlart #stylegan2 #stylegan2ada #MachineLearning #generativeart
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
#StyleGAN2 pokemon sprites after being fed through https://t.co/QPHaoyZ90b
Seven hours (300 kimg) into training a pokemon #StyleGAN2 model from scratch
A gorgeous bunch of watercolours generated using Stylegan2. Trying to pick the best from these to create the videos for the "Ode" series: https://t.co/e0TIU2BnSS
#raredigitalart #digitalpainting #cryptoart #eth #watercolour #ai #ArtificialIntelligence
@runwayml @makersplaceco
StyleGAN2を使った自動生成の続きで、今回はDanbooru2018データセットを試してみました。以下から顔部分の切り抜き済みデータをお借りしています。
https://t.co/VmfudvpqGK
学習時間は前回と同じくローカルGPUで20時間程度。溶けている部分や過学習っぽいキャラもいるのでまだ調整は必要そうですね。
More #StyleGAN2 stochastic weight average examples. The middle image shows the average of the left and right. Script (swa .py) is here in Peter's StyleGAN2 fork: https://t.co/4tMan2xx4M
@pbaylies credits @davidstap @robertluxemburg @Veqtor and @theshawwn - Thanks for sharing!
Cursed StyleGAN2 people after a deep style transfer, makes some interesting things