[louprado]

As you suggested, continuity of appearance is what makes this problem so difficult.

I recall watching a movie that was converted from black-and-white to color as a child. There were many distracting artifacts. Most notable was the hairlines of the actors would shift as the actor rotated their head. It made the film unwatchable.

[nuclai]

(Author here.) Absolutely! Using multiple super-resolution networks, not only continuity would present problems, but also blending between different regions. I agree there's a lot of value for domain-specific networks here, as you can see from the faces example on GitHub.

I'd be curious to see an ensemble-based super-resolution, where each model can output the confidence of a pixel region, then have another network learn to blend the result.

Conversely, these results are achieved using a single top-of-range GPU. Everything fits in memory for a batch-size 15 at 192x192. By distributing the training somehow, you could make the network 10x bigger and train for a whole week and likely get much better general purpose results.