mrlibw/ControlGAN

ControlGAN represents a historical milestone in the evolution of text-to-image synthesis, specifically from the pre-diffusion era (circa 2018). While it introduced important concepts like word-level spatial attention to provide more fine-grained control than its predecessor AttnGAN, the technology is now functionally obsolete. Modern Diffusion models (Stable Diffusion, DALL-E 3) and specialized control layers (ControlNet) have vastly surpassed the image quality, diversity, and prompt adherence of GAN-based architectures. With 170 stars and zero activity for several years, the project serves primarily as a research archive. There is no defensibility; any modern practitioner would use a Diffusion-based approach or a Diffusion Transformer (DiT). The displacement has already occurred, and frontier labs have integrated these capabilities into multi-modal models that treat image generation as a native feature rather than a niche research task.