Synthetic-to-realistic image conversion using generative adversarial network (GAN) or other machine learning model

Abstract

A method includes obtaining training data having first image pairs, where each of the first image pairs includes (i) a first training image and (ii) a first ground truth image. The method also includes training a machine learning model to generate realistic images using the first image pairs. The method further includes obtaining additional training data having second image pairs, where each of the second image pairs includes (i) a second training image and (ii) a second ground truth image. At least some of the images in the second image pairs are less aligned or of lower quality than at least some of the images in the first image pairs. In addition, the method includes continuing to train the machine learning model to generate the realistic images using the second image pairs.

CPC Classifications