Segmentation guided image generation with adversarial networks

Embodiments provide methods and systems for image generation through use of adversarial networks. An embodiment trains an image generator comprising (i) a generator implemented with a first neural network configured to generate a fake image based on a target segmentation, (ii) a discriminator implemented with a second neural network configured to distinguish a real image from a fake image and output a discrimination result as a function thereof and (iii) a segmentor implemented with a third neural network configured to generate a segmentation from the fake image. The training includes (i) operating the generator to output the fake image to the discriminator and the segmentor and (ii) iteratively operating the generator, discriminator, and segmentor during a training period, whereby the discriminator and generator train in an adversarial relationship with each other and the generator and segmentor train in a collaborative relationship with each other.