The generator produces fake images which are further differentiated by discriminator whether the image is real or fake. GAN has a generator and a discriminator network.
To produce a realistic appearance with an enhanced vision of face image, a fusion-based Generative Adversarial Network approach is used. So, the proposed work is focused on these key issues using Generative Adversarial Networks (GANs). Several techniques are available for face age progression still identity preservation as well age estimation accuracy are big challenges and need attention.
