[lqdc13]

I think for cubism, the easiest way would need to create the "original" painting/image before cubism transformation and learn the transformation.

Ideally several such images to not overfit on the specific details of that transformation.

The other way is to get a huge dataset of cubism still life paintings and also a dataset of a bunch of photographs of still life and learn the "average" transformation from that. Although such transformation may not generalize to other subjects and might only work well with flowers/food on a table.

Same thing with the other styles. For example (NSFW), photographs of naked women such as https://www.daniel-bauer.com/images/art_nudes/15_artistic_nu... transformed into classical https://www.google.com/culturalinstitute/beta/asset/the-birt... Here you would first identify the people objects and then learn the transformation of both people and backgrounds.

Still, the current approach works fine for things like starry night because of the nature of the painting.