[Jack000]

I think logos are a tough problem for convnets because they're not very compositional - ie. they're not made of heirarchically nested parts.

the space of logos is also probably not continuous - eg. there is a logo in the latent space between nike and apple, but it's unlikely to be aesthetic.

[posterboy]

Nipple? Apik? Could be a sportswatch. There might be a few clusters along the path through latent space (if that makes any sense, just skimmed the paper mostly for the figures).

The attempt here seems to be really naive, I agree. But why are logos not compositing? Coat of arms are frequently described in such a manner that would allow to mix them. But then, the traditional artistic combinations of different ones into new are not mere half way morphs. And a classic logo needs to be compositional, because it's easier to perceive (decompose), e.g. hammer and sickle. Scientific Icons are frequently using mathematical patterns and plots, which tickle the eye in quite a different manner. I thought the nike swoosh comes from that rather abstract direction, whereas the apple is quite objective. Both are pictographs, but only the apple is a logo (from logos, ie. speaking).

[Jack000]

there are logos that are compositional, but most logos are abstractive - eg. the hammer and sickle logo only makes sense because we have prior knowledge of what hammers and sickles look like. You could learn an abstract representation of hammers from a dataset of hammers, but not from a dataset of logos.

I think GANs work best on images with hierarchical composition like human faces.