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https://github.com/junyanz/CycleGAN https://github.com/junyanz/CycleGAN

• dr_zoidberg 9y ago
  GANs and style transfer are not the same as being able to recognize and imagine changes on the representation you just learned. Also, look at the GAN examples: even the water in the background is being affected by the "horse to zebra" transfer. You can perfectly imagine a brown horse, standing in the beach, and then being told "now iamgine the horse is white" without than "instruction" affecting how you imagine the beach.
  • MrQuincle 9y ago
    Perhaps explain what your preferred dataset is. + Brown horses on beaches + Some way to indicate "white" "horse". If you have a good idea about how we can train for your problem, I'm not so convinced that it cannot be solved.
    • dr_zoidberg 9y ago
      No, the problem I was pointing at is that you want to change a part of the image (horse into zebra), but the style transfer GAN learned to map pixels from one space into another. So it knows it has to change the colour of some things, and add stripes here and there, and also probably there too. But it isn't consistent with the stripes (you can see in some gifs how the pattern suddenly changes and adjusts), and it doesn't recognize (segment) the horse as the only relevant thing that has to be changed. But that's not bad per se about style transfer. It's an interesting technique, but if you want to convert all horses to zebras in an image, that seems to be a bit too general for current-generation GAN architectures. Maybe it can be improved upon, or a different, novel architecture is required, and not just something you can solve by throwing more data at it.
      • MrQuincle 9y ago
        Yes, the segmentation could be better. I still think you're not pointing out fundamental issues though. :-)