SNGAN (Spectral Normalization GAN)

Spectral Normalization GAN (SNGAN) is a type of generative model designed to create realistic images. It improves training stability by normalizing the neural network's layers using spectral normalization, which controls the strength of transformations, preventing the model from becoming unstable or generating poor images. This technique ensures the neural network's discriminator (which judges image realness) operates within stable bounds, leading to more consistent and higher-quality generated images. Overall, SNGAN combines spectral normalization with GAN architecture to produce sharper, more realistic visuals while maintaining stable training behavior.