Yona Coscas, Elbit Systems Aerospace
Generating Photo-realistic Images from Simulation

Our work offers a new method for generating photo-realistic images from semantic label maps and Computer Graphic (CG) simulation edge map images. We train a Generative Adversarial Network (GAN) in a conditional way to output a photo-realistic version of a given CG scene. Existing architectures of GANs still lack the photo-realism capabilities needed to train DNNs for computer vision tasks, we address this issue by embedding edge maps, and training it in an adversarial mode. We also offer an extension to our model that uses our GAN architecture to create visually appealing videos.