We present an approach to enhancing the realism of synthetic images. The images are enhanced by a convolutional network that leverages intermediate representations produced by conventional rendering pipelines. The network is trained via a novel adversarial objective, which provides strong supervision at multiple perceptual levels. We also introduce multiple architectural improvements in the deep network modules used for photorealism enhancement.

2021: Stephan R. Richter, Hassan Abu Alhaija, V. Koltun

https://arxiv.org/pdf/2105.04619.pdf