Generative Adversarial Network
Two networks — a generator and a critic — trained against each other.
In a GAN, a generator tries to produce realistic data while a discriminator tries to tell real from fake; the two improve in competition. GANs produced the first strikingly realistic synthetic images and dominated generative imaging before diffusion models took over.