Consider a generative adversarial network for faces. Photos have let's say some unique scars A successful model could create faces with scars in them. But not

Consider a generative adversarial network for faces. Photos have let's say some unique scars A successful model could create faces with scars in them. But not the exact scar and face and background that they trained on without additional information. What you are looking for is mutual information between the images not compression Yes you could use a very well trained GAN for face compression. But a GAN model itself would not be able to reconstruct its training input without being shown the images again