AI&Creativity: Visual Anarchist Realism of CycleGAN (and how AI cheats on developers)
You already tried out transforming photos into a painting by Van Gogh. But have you ever imagined the other way round? I mean, transforming painting into photos? While the first attempt is close to a filter function (visuals are adjusted and style is transfered, so you can recognize specific artistic character), the second one appears to be nearly impossible. Bringing to reality an artistic phantasy. Pygmalion would be proud.
Wrong. It’s possible now. With CycleGAN.
The principle of this process is already containing in the title — and in the paper “Unpaired Image-to-Image Translation using Cycle-Consistent Adversarial Networks”. A huge difference to previous attemps is in following:
Image-to-image translation is a class of vision and graphics problems where the goal is to learn the mapping between an input image and an output image using a training set of aligned image pairs. However, for many tasks, paired training data will not be available. We present an approach for learning to translate an image from a source domain X to a target domain Y in the absence of paired examples.
The cycled process can allow the transition between styles and other visual aspects of an image with consistent data…
