Home Projects Attend-and-Excite
Attend-and-Excite
Jupyter Notebook

Attend-and-Excite

Official Implementation for "Attend-and-Excite: Attention-Based Semantic Guidance for Text-to-Image Diffusion Models" (SIGGRAPH 2023)

by yuval-alaluf · GitHub
Stars
Forks
License
Created
Last commit
diffusion-modelsstable-diffusiontext-to-imageMITJupyter Notebook
View on GitHub
In plain words

Generate images from text descriptions using an advanced AI model that improves image quality.

You maintain this project?

Claim its page: indexed whatever its rank, translated into six languages, and enriched with what you write yourself.

Claim this page →
Attend-and-Excite — GitHub preview card
📈 Star history
773772
2026-07-202026-08-31
📈 Track Attend-and-Excite

Get an email alert on its next release or when it starts trending — never miss the moment.

Free · no card · unsubscribe anytime
Get email alerts →
📄 About

Official Implementation for "Attend-and-Excite: Attention-Based Semantic Guidance for Text-to-Image Diffusion Models" (SIGGRAPH 2023)

Attend-and-Excite has 772 stars on GitHub. It has been forked 63 times. Attend-and-Excite is written mainly in Jupyter Notebook. It has been in active development since 2023. Attend-and-Excite is available under the MIT license. Its main topics are diffusion-models, stable-diffusion, text-to-image.

Frequently asked questions

What is Attend-and-Excite?

Official Implementation for "Attend-and-Excite: Attention-Based Semantic Guidance for Text-to-Image Diffusion Models" (SIGGRAPH 2023)

Is Attend-and-Excite open source?

Attend-and-Excite is an open-source project. It is released under the MIT license.

Is Attend-and-Excite free?

Yes. Attend-and-Excite is free and open source — you can use, modify and self-host it.

What license does Attend-and-Excite use?

Attend-and-Excite is available under the MIT license.

What language is Attend-and-Excite written in?

Attend-and-Excite is written mainly in Jupyter Notebook.

🏅 Maintainer of this project?
olud.ai badge — Attend-and-Excite

Add this live badge to your README — your GitHub stars and directory rank, refreshed daily.

[![olud.ai](https://olud.ai/badge.php?tool=yuval-alaluf-attend-and-excite)](https://olud.ai/project/yuval-alaluf-attend-and-excite.html)
More badge options →
🧬 Shares DNA with🧬 View the DNA map →
e4t-diffusion
Implementation of Encoder-based Domain Tuning for Fast Personalization of Text-to-Image Models
324 · deep-learning
sharestext-to-imagestable-diffusion
MACE
[CVPR 2024] "MACE: Mass Concept Erasure in Diffusion Models" (Official Implementation)
393 · diffusion-models
sharestext-to-imagestable-diffusion
stable-diffusion-aesthetic-gradients
Personalization for Stable Diffusion via Aesthetic Gradients 🎨
741 · diffusion-models
sharestext-to-imagestable-diffusion
mixture-of-diffusers
Mixture of Diffusers for scene composition and high resolution image generation
449 · ai
sharesstable-diffusiondiffusion-models
flux-krea
Official GitHub repository for FLUX.1 Krea [dev].
364 · diffusion-models
sharestext-to-imagediffusion-models
Dreambooth-Stable-Diffusion
Implementation of Dreambooth (https://arxiv.org/abs/2208.12242) with Stable Diffusion
7.7k · pytorch
sharestext-to-imagestable-diffusion
awesome-text-to-image-studies
A collection of awesome text-to-image generation studies.
760 · artificial-intelligence
sharestext-to-imagediffusion-models
TokenFlow
Official Pytorch Implementation for "TokenFlow: Consistent Diffusion Features for Consistent Vi…
1.7k · iclr2024
sharestext-to-imagestable-diffusion
Wuerstchen
Official implementation of Würstchen: Efficient Pretraining of Text-to-Image Models
555 · diffusion-models
sharesstable-diffusiondiffusion-models
CrossAttentionControl
Unofficial implementation of "Prompt-to-Prompt Image Editing with Cross Attention Control" with…
1.3k · cross-attention
sharesstable-diffusiondiffusion-models

Measured from GitHub topics shared by both projects, weighted by how rare each topic is.