Unconditional Image Generation

Unconditional image generation — producing realistic images from pure noise — is the purest test of a generative model's learned distribution. GANs dominated for years (ProGAN, StyleGAN, StyleGAN3 pushed FID below 2 on FFHQ), but diffusion models dethroned them in both quality and diversity starting with DDPM (2020). The FID metric itself is now questioned as models produce images indistinguishable from real photos. Historically the proving ground for new generative architectures, though the field's energy has largely migrated to conditional generation (text-to-image) where practical applications live.