I'm playing around with the use of deep learning on images and done quite works : colorizing black and white images for example, or maybe fixing old damaged photos.

Today I want to tackle a new problem, concerning the conversion of sketches into real look like images as shown in the figure.

input is a sketch and the output should be an image corresponding to the input

Performing this could be done in various ways. I want to know if it is correct to think of CycleGANs for this task, since in truth they are not made trivially for that, and the pros and cons for CycleGANs and AutoEncoders for such task.

PS: Generating data is not a big deal for me, I have already a large database, and the right scripts to do the conversions in the both directions.


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