> I assume that this would only work reliably for headshots/avatars? StyleGAN works best on single centered objects which are not too diverse in shape. So head

> I assume that this would only work reliably for headshots/avatars? StyleGAN works best on single centered objects which are not too diverse in shape. So heads work great if you align them to the middle, and you can get OK results with single centered figures like someone standing, but anything beyond that and it falls apart. We have a theory about that (https://github.com/tensorfork/tensorfork/issues/21 https://github.com/tensorfork/tensorfork/issues/21) but we've long since moved onto BigGAN, which can model much more diverse datasets like ImageNet successfully. As far as fursonas go, see my other comment: https://news.ycombinator.com/item?id=23096442 https://news.ycombinator.com/item?id=23096442 I'd say that GANs are better at letting someone explore fursonas than any human artist is or ever will be. You cannot click a button and have a human artist generate 32 variants in a second for you, toggle on or off attributes, nor can they slide a slider from 'human' to 'neko' to 'dangerously cheesy!'. You might pay for a commission of your final fursona for the highest-quality image with no artifacts, but for exploring...? And as NNs get better over time, they'll creep up the value chain, as it were. (I'm still a little shocked how good the human voices in OpenAI's Jukebox https://openai.com/blog/jukebox/ https://openai.com/blog/jukebox/ are, even if the highest level of abstraction is still very shaky and they need to tack on another layer or two to get choruses etc.)