I always did wonder how much StyleGAN was compositing existing features rather than generating wholly distinct features.

With real human faces it's almost impossible to tell but with these you can definitely pick a character per feature.

Begs the question at what point does ownership change. Can I trace batman but change his hair color? what about just his face? or just his mouth? Can I cut and paste a bunch of superheroes together and claim it as my own? etc

This will certainly be the crux of intellectual property lawsuits in the future.

It's striking that some of these examples have distinct features from specific, identifiable datasets: we can occasionally recognize specific characters (the old man from Pixar's UP is getting mentioned a lot), but it also reproduces more general aesthetic patterns. Even when I can't recognize the source data, I can distinctly see in some of these faces "the Pixar look", and in others "the DreamWorks look".

Were I an IP lawyer, I would start thinking of arguments along the lines of "this technology simply obfuscates the source of plagiarisms". I would also start to think about trying to force anyone who uses this technology to disclose the sources of their training data, since a model trained largely on "the Pixar look" could be benefiting from Pixar's character design processes without having to hire any of Pixar's artists.

And, if I were philosophically inclined, I would also start thinking about how this is any different from hiring a random artist and instructing them to "design characters that look like Pixar characters".

I suspect that one key difference is that the human artist's success can't easily be measured, but the GAN's success can very easily be measured.

At some point big producers like Pixar will probably use something like StyleGAN to extend their copyright coverage. E.g. generate as many variations as they can, which then all fall under their own copyright.

So in the end this technology might not be as "liberating" as people think it is.

Not if a tech firm gets there first. Imagine the productive and legal power being in the algorithm.

In a way, this is a much better setup for artists and creatives. There isn't some giant licensing firm controlling your work. You simply buy or rent the best tools to make your work.

That said, it'll only be good for creatives and consumers if there is sufficient competition. And open source equivalents that still enable creation.

Wouldn't it make more sense to use a density based model and then describe some hull centered around your original creation?

I guess that's the big debate around GitHub Copilot and open source code, especially GPL (but also others).

The rights surrounding caricatures may provide some insight here. I know some celebrities are particularly vigilant about keeping unapproved photos of their faces out of circulation but they probably wouldn't have the same success with a hand-drawn likeness or caricature.

I think that would depend on the license of each image on the dataset that influenced the output image. maybe not but it would make sense to be this way