Generator: the generator generates new data instances that are "similar" to the training data, in our case celebA images. Generator takes random latent vector and outputs a "fake" image of the same size as our reshaped celebA image. Discriminator: the discriminator evaluate the authenticity of provided images; it classifies the images from the generator and the original image. Discriminator takes true of fake images and outputs the probability estimate ranging between 0 and 1. Here, D refers to the discriminator network, while G obviously refers to the generator.
Sep-16-2021, 15:20:08 GMT