AI RESEARCH
Image Generation Models: A Technical History
arXiv CS.CL
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ArXi:2603.07455v1 Announce Type: cross Image generation has advanced rapidly over the past decade, yet the literature seems fragmented across different models and application domains. This paper aims to offer a comprehensive survey of breakthrough image generation models, including variational autoencoders (VAEs), generative adversarial networks (GANs), normalizing flows, autoregressive and transformer-based generators, and diffusion-based methods.