hu-zijing/AsynDM
[ICLR 26] Asynchronous diffusion models allocate individual pixels with varying timestep schedules, yielding improved text-to-image alignment.
This project helps graphic designers, marketers, and content creators generate images from text descriptions with greater accuracy. You provide a text prompt describing an image, and it outputs images that align more faithfully with your original intent, especially for detailed or specific elements. It's for anyone who uses text-to-image AI to create visual content and needs higher precision.
No commits in the last 6 months.
Use this if you find that AI-generated images often miss key details or misinterpret parts of your text prompts, especially for complex scenes or specific object placements.
Not ideal if you are looking for a basic text-to-image generator and do not prioritize extreme precision in image-to-text alignment.
Stars
18
Forks
1
Language
Python
License
MIT
Category
Last pushed
Oct 07, 2025
Commits (30d)
0
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