It's an old idea really, or a collection of old ideas with a NN twist. Not really clear how much that latter bit brings to the table but interesting to think a

It's an old idea really, or a collection of old ideas with a NN twist. Not really clear how much that latter bit brings to the table but interesting to think about. The "dictionary" approach was roughly what vector quantization was all about. The idea of turning lossy encoders into lossless by also encoding the error is a old one too, but somewhat derailed by focus on embedable codecs with an ideal of each additional bit read will improve your estimate. I think the potentially novelty here is really in the unfortunately-named-but-too-late-now super-resolution aspects. You could do the same sort of thing ages ago with say IFS projection, or wavelet (and related) trees, or VQ dictionaries with a resolution bump, but they were limited by the training a bit (although this approach might have some overtraining issues that make it worse for particular applications.