I don't know - the second Picasso/Brad Pitt would make for a good instagram filter.
I think if there was some level of semantic tagging and weighting of different aspects of an artist's technique it might do better - identify sky, water, buildings, faces, plants, etc (none of which is particularly beyond the capability of current image classifiers), then it might produce better results. I could easily imagine this turning into a 'Rembrandtize Me' selfie-filtering app.
Then it's really only a matter of time before the extension of these techniques moves to 'make my vacation photos look like they were taken by Ansel Adams', then 'show me Star Wars as if Alfred Hitchcock had directed it', or 'play me Smells Like Teen Spirit as if it had been sung by Elvis'. Neural Remixing.
Author here. The examples with the golden gate bridge were generated using an earlier version of the code; later additions (L-BFGS vs SGD, TV regularization) tend to clean up the cross-hatch pattern quite a bit.
Comments
The "Scream" version of the Golden Gate bridge looks amazing.
The Scream versions are the only ones I find particularly interesting. All the others seem to fall victim to prominent cross-hatch patterns.
I don't know - the second Picasso/Brad Pitt would make for a good instagram filter.
I think if there was some level of semantic tagging and weighting of different aspects of an artist's technique it might do better - identify sky, water, buildings, faces, plants, etc (none of which is particularly beyond the capability of current image classifiers), then it might produce better results. I could easily imagine this turning into a 'Rembrandtize Me' selfie-filtering app.
Then it's really only a matter of time before the extension of these techniques moves to 'make my vacation photos look like they were taken by Ansel Adams', then 'show me Star Wars as if Alfred Hitchcock had directed it', or 'play me Smells Like Teen Spirit as if it had been sung by Elvis'. Neural Remixing.
Author here. The examples with the golden gate bridge were generated using an earlier version of the code; later additions (L-BFGS vs SGD, TV regularization) tend to clean up the cross-hatch pattern quite a bit.