Image-Super-Resolution-via-Iterative-Refinement

I am afraid these methods ("learn the typical detail and "re"-apply it") on the said context ("obtain telling detail where we miss it") would be "dreaming" the detail. There methods are for "beauty", not to "induce real facts": what is "probable" is not what is "real". -- Edit: I have an example for you. Check https://github.com/Janspiry/Image-Super-Resolution-via-Itera... and notice the black spot under the iris of the right eye, on the left: does the actual person really have it? It is not in the blurred source image, https://github.com/Janspiry/Image-Super-Resolution-via-Itera... . Now think of an "empiricist" perceptive instrument returning that kind of "noise"... -- I understand you work on the topic (ANN for assessment), so you surely meant something different that what contextually appears.

Here's an unofficial copy of the code: https://github.com/Janspiry/Image-Super-Resolution-via-Itera...

https://github.com/Janspiry/Image-Super-Resolution-via-Itera... is an open-source implementation

Here an unoffical implementation https://github.com/Janspiry/Image-Super-Resolution-via-Itera... Imagine a game using this tech, you could render a game in a lower resolution and possible get a better looking game. But then again they aren't yet dealing with temporal data. In the previous discussion https://news.ycombinator.com/item?id=27858893 they mentioned that it was only class conditional but it also seems to work on unconditional data.