[vintermann]

It's right that it needs additional information to distinguish style from content, but they get that from selected layers from established, pre-trained neural nets for image recognition. I don't entirely understand why it works myself, but it seems to.

[brian_cloutier]

From the way you described it, you could consider the pre-trained network to be the "missing image". It already has an idea of what images should look like so when it detects an object the "style" is what makes that object different than the stereotypical one it's already modeled.

[vintermann]

Right. But it's more complicated than that, the choice of layer(s) to use matters a lot, and I have no idea why they do as they do. Seems it's a bit of dark magic to get it to work well - takes lot of aesthetic judgements too.

I think Alex J. Champandard's implementation is probably the best one out there right now. It has a ton of knobs to twist and is very fast.