Generative Adversarial Networks - What is the difference between RNN and GAN?

A Generative Adversarial Network (GAN) consists of a Generator and a Discriminator, which work iteratively in an adversarial process where the Generator attempts to trick the Discriminator into misclassifying 'real' and 'fake' images. Recurrent Neural Networks (RNNs), in contrast, have a different structure from standard 'feed forward' neural networks, as they incorporate data feedback loops.