[aab0]

One idea here is to adopt a recent generative approach: a CNN which starts with two noise image inputs, and then repeatedly tweaks it plus a new noise image over multiple inputs until it does one last tweak to a final version. The noise serves as a RNG for making choices to the built-up image, I think. You could apply this recurrent idea to movies too: for the first BW frame, pass in a noise image and the BW frame, get out a C frame; now for the second BW frame, pass in the BW frame but also the C frame from before. The CNN may gradually learn to transfer colors from the C frame to the BW frame, thereby maintaining temporal coherency.

(Or you could just try to use a RNN directly and keep hidden state from frame to frame.)