A thought I had while reading about this was what is the limit to upscaling via this method? By that I mean if one where to just keep upscaling and had a monitor capable of displaying the image, how long until the image became unrecognizable? Surely upscaling an already upscaled image would result in some strange artifacts.
You'll end up seeing more and more of the training set. You might zoom in on a newspaper on a desk through a window across the street reflected off the windshield of a car and get perfectly legible text, but it's just going to have whatever lorem ipsum headlines were used to train the net.
> Make one good enough and it can fill in the blanks properly.
I would say it can fill in the blanks likely or plausibly. But one can't guarantee that it is the proper or real content, since the neural net is imagining / inventing the upscaled version.
Sure. I'm not saying it will represent reality 100%, but it could be good enough that you probably couldn't tell the difference.
Current neural nets might perhaps not be able to upscale with no limit and still make it look good, but it's not like it can't be done. A good human artist could take a small grainy image and given enough effort draw an upscaled version that would be a very reasonable representation of what a larger image would have looked like, there's no reason to believe that artificial neural networks can't do the same.
