If you could take a Bayesian perspective toward the super-resolution problem, things will make sense: given a low-res image, it corresponds to a distribution of corresponding high-res images. Which one is more likely? It depends on the prior and the likelihood. The right figure is a possible outcome, however, if we have strong prior toward the possibility of well-known people, we would be biased toward those people. It's not wrong, it is just not comprehensive.
PoignardAzur|4 years ago
Even without "famous person bias", it's fair to say that the skin tone of the resolved image is slightly but measurably lighter than the skin tone of the blurred original (I'm curious what the blurred version of the resolved image looks like, btw).
Occam's razor says the model simply wasn't trained with enough ethnically diverse images, for whatever reason.