yuval-alaluf/Attend-and-Excite
Official Implementation for "Attend-and-Excite: Attention-Based Semantic Guidance for Text-to-Image Diffusion Models" (SIGGRAPH 2023)
This project helps artists, designers, and marketers who use AI to generate images from text descriptions. It improves the reliability of image generation by ensuring all key elements and their specific attributes from a text prompt (e.g., 'a red car and a blue bike') appear correctly in the final image. You input your desired text prompt and get back a more accurate, high-quality image that faithfully represents every detail you asked for.
767 stars. No commits in the last 6 months.
Use this if you are generating images from text prompts and find that the AI frequently omits specific objects or incorrectly applies attributes (like colors) to the wrong subjects.
Not ideal if your image generation needs are basic and don't require precise control over multiple objects or their exact attributes within a single prompt.
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767
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64
Language
Jupyter Notebook
License
MIT
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Last pushed
Jan 26, 2024
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