🎨 GAN Generator Playground

Generative Adversarial Networks (GANs)

Concept: Two neural networks compete - Generator creates fakes, Discriminator tries to detect them

Training: Minimax game. Generator improves at creating realistic images, Discriminator gets better at detection

Convergence: When Discriminator can't distinguish real from fake (50% accuracy)

Types: DCGAN • StyleGAN • CycleGAN • Pix2Pix

Applications: Image generation • Super-resolution • Style transfer • Data augmentation • Face aging