• Devidatt Joshi
• Dr. Anil gupta

Image to image translation is a new sensation in the field of machine learning, artificial intelligence, and vision communities. The principle of an image-to-image translation is to convert an image of the source domain to a target domain image. Recent innovations and techniques have shown remarkable success in the field of an image to image translation for two domains. But the existing methods have limited functionality and methods when we perform translation between more than two domain images. Here, GAN (Generative Adversarial Network) plays a vital role, GAN provides us functional approach that can perform image-to-image translation between multiple domains using a single conversation model. This paper empirically discusses and analyzes image-to-image translation using GAN.

Image-to-Image translation, GAN, Generative models, Image datasets.

"GAN: Era of Image to Image translation ", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.8, Issue 6, page no.b473-b476, June-2021, Available :http://www.jetir.org/papers/JETIR2106204.pdf

"GAN: Era of Image to Image translation ", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.8, Issue 6, page no. ppb473-b476, June-2021, Available at : http://www.jetir.org/papers/JETIR2106204.pdf