Generative Adversarial Networks for Image Segmentation

摘要

A method is provided of training a generative adversarial network for performing semantic segmentation of images. The generative adversarial network includes a generator neural network and a discriminator neural network. The method includes providing an image as input to the generator neural network, receiving a predicted segmentation map for the image from the generator neural network, providing i) the image, ii) the predicted segmentation map, and iii) ground-truth label data corresponding to the image, as distinct training inputs to the discriminator neural network, determining a set of one or more outputs from the discriminator neural network in response to said training inputs, and training the generator neural network using a loss function that is a function of said set of outputs from the discriminator neural network.