“(GANs), and the variations that are now being proposed is the most interesting idea in the last 10 years in ML, in my opinion.”
Yann LeCun, Director of AI Research, Facebook
- Neural networks have made great progresses in the fields of image recognition…
- But tasks where human creativity is needed (e.g. generating a new image) are far from being solved;
- GAN are making some of these tasks possible.
What is a GAN:
A GAN can be seen as the relation between a forger and an investigator.
- The forger objective is to create fraudulent imitations of original paintings by famous artists;
- The investigator (which knows the properties which sets the original artist apart) must identify the fake paintings;
- Both the forger and the investigator will try to become more and more capable than the other part as the time goes on.
A GAN is composed by two main components :
- The basic idea of GANs is to set up a game between Generator and Discriminator.
We use gan to generate fashion images, to perform style tranfer and we try to modify their architectures to improve the generation.
MetalGAN: a Cluster-based Adaptive Training for Few-Shot Adversarial Colorization – ICIAP 2019 (under review)
Tomaso Fontanini is the supervisor for this project.