LocoGAN -- Locally Convolutional GAN

We add extra channels with spatial information to the input noise images. In the paper we construct a fully convolutional GAN model: LocoGAN, which latent space is Such architecture and design of latent space allows us to given by noise-like images of possibly different use an input of various dimensions. We use that to train our resolutions. The learning is local, i.e. we process model only on parts of the latent image, see Figure 1. We call not the whole noise-like image, but the subimages this approach local learning. Section 3 contains the detailed of a fixed size.