Dynamic-Pix2Pix: Noise Injected cGAN for Modeling Input and Target Domain Joint Distributions with Limited Training Data. (arXiv:2211.08570v1 [cs.CV])

Learning to translate images from a source to a target domain with
applications such as converting simple line drawing to oil painting has
attracted significant attention. The quality of translated images is directly
related to two crucial issues. First, the consistency of the output
distribution with that of the target is essential. Second, the generated output
should have a high correlation with the input. Conditional Generative
Adversarial Networks, cGANs, are the most common models for translating images.
The performance of …

arxiv data modeling noise pix2pix training training data