51–53 of 53 posts
Granted it won't be actually sharpening the images but for 99% of the use cases it would be awesome!
(Author here.) Unlike most other non generative adversarial network (GAN) approaches to super-resolution, it does try to inject high-frequency detail; see the faces example on GitHub. But I tuned down that parameter in the released models a bit so it performed better generally.
This approach can be equaled or bettered with no machine learning. This example allows easy comparison between common techniques. Choose image 7 to see an example with a person: https://dl.dropboxusercontent.com/u/2810224/Homepage/publica...
We enhanced the image like on CSI and look, the defendants face! "Because my photos were used heavily in the dataset..." Jury: So guilty
Defense should train a network with faces of the jury and then show how the same technique, run by their biased network, now shows each of them in the scene of the crime :)