I would go for decrappify: https://www.fast.ai/2019/05/03/decrappify/ https://www.fast.ai/2019/05/03/decrappify/ GAN's are hard to train for a new ML practitio

I would go for decrappify: https://www.fast.ai/2019/05/03/decrappify/ https://www.fast.ai/2019/05/03/decrappify/ GAN's are hard to train for a new ML practitioner, VAE can have blurry results if you are not using skip-connections like in U-NET. It sounds like you have training examples (images pre and post processing), but would benefit from an approach using transfer learning since you don't have that many. Good luck!