This is a great topic.
I did some pixel art upscaling in a similar way, just didn't use neural nets but classical pixel art upsaling algorithms found in emulators etc. That created a good initial version which I then manually adjusted in GIMP. (BTW if someone wanted to use machine learning to create algorithms for a better automatic pixel art upscaling, I'd be very interested.)
I think fore the best quality you always have to manually edit the result of automatic upsace, even that generated by a good neural net. The amount of manual work will of course be much smaller than complete upscale by hand.
With machine learning such as the programs you used I see a few potential issues and dangers with copyright -- I don't know if that's the case, but I suppose that if a non-public domain dataset is used to train the net, then the images it will generate may end up being a derivative work of a copyrighted work, i.e. the images in the dataset, so they may be either non-free, or may be burdened by the dataset license. This probably depends on each specific case, but I think the danger is there. Does anyone know anything about this?
Also compiling and using all the these machine learning tools is not very easy, I remember having had hard time setting up a style transfer program and in the end was only able to use the SW (non-GPU) implementation, because I didn't want to use any proprietary drivers and technologies, so the program was slow and unusable. There are web tools but they insert watermarks and have various ugly conditions on what you can do with the results etc. Does any simple, good, offline, fast and free as in freedom tool exist for this? With such tools more artist would definitely do this.
