What This Research Area Covers
Image generation research studies models that produce images from text descriptions or other inputs, spanning diffusion-based methods (the dominant current approach) and earlier techniques like generative adversarial networks (GANs).
Why It Matters
Text-to-image generation has become one of the most visible and widely-adopted AI capabilities, with substantial creative, commercial, and design applications.
Current Research Directions
Improving prompt adherence (generating exactly what was described), better handling of text and fine detail within images, and more efficient generation requiring less compute per image are active areas.
Related Pages
Frequently Asked
What's the dominant current technique for image generation?
Diffusion models are currently the dominant approach, having largely superseded earlier GAN-based methods for most leading systems.
What was DALL-E's significance?
An early, influential text-to-image model that helped popularize the technique broadly — see our OpenAI research page.
Where can I find image generation tools to try?
See our Tools directory.
Where can I find image generation prompts?
See our Prompts library's Image Generation category.