We give an overview of the different rendering methods and we demonstrate that the use of a Generative Adversarial Networks (GAN) for Global Illumination (GI) gives a superior quality rendered image to that of a rasterisations image. We utilise the Pix2Pix architecture and specify the hyper-parameters and methodology used to mimic ray-traced images from a set of input features. We also demonstrate that the GANs quality is comparable to the quality of the ray-traced images, but is able to produce the image, at a fraction of the time.
@article{arxiv.2110.12039,
title = {Generative Adversarial Networks for Non-Raytraced Global Illumination on Older GPU Hardware},
author = {Jared Harris-Dewey and Richard Klein},
journal= {arXiv preprint arXiv:2110.12039},
year = {2021}
}