----- CONTENT -----

obtain future art prediction (linear trend only, no VAR) by following the steps:

• (1) use Classifier.py on the tinyImageNet dataset to train auxiliary classifier model.

• (2) use WikiArt_crop.py then WikiArt_select_20_movements.py to produce art dataset. Make two versions: 64x64 and 128x128.

• (3) use AE_perceptual with style and/or content loss to obtain the latent codes. Use the 64x64 version of the art dataset for this task.

• (4) use CGAN_128.py to train the conditional GAN using the aforementioned images and codes.

• (5) use Generate_future to make future art.

----- links to WikiArt contemporary examples -----

Post-Minimalism:

• https://www.wikiart.org/en/gego/untitled-1980
• https://www.wikiart.org/en/christopher-wilmarth/the-whole-soul-summed-up-1979
• https://www.wikiart.org/en/james-lee-byars/dress-for-five-persons-1969
• https://www.wikiart.org/en/takamatsu-jiro/jiro-takamatsu-1983

New Casualism:

• https://www.wikiart.org/en/raoul-de-keyser/untitled-2004
• https://www.wikiart.org/en/raoul-de-keyser/sketchy-cobaltic-blue-flag-2009
• https://www.wikiart.org/en/raoul-de-keyser/wait-2006
• https://www.wikiart.org/en/raoul-de-keyser/untitled-2006-1