Divide & Bind Your Attention for Improved Generative Semantic Nursing

:fire: Official PyTorch implementation for paper 'Divide & Bind Your Attention for Improved Generative Semantic Nursing' (BMVC 2023 Oral)

:fire: Updates: We update our Divide & Bind pipeline, which is now compatible with Diffusers 0.21.4!

Getting Started

Our environment is built on top of Stable Diffusion:

conda env create -f environment/environment.yaml  
conda activate ldm

Additional required packages are listed in environment/requirement.txt.

Stable Diffusion v1.5 model can be found here.

Generation

• generate_images.ipynb provides an example on how to generate images using Divide & Bind.
• examples_generation.ipynb provides some prompts and seeds used in the paper. Example images are saved in example_outputs.

Citation

If you use this code please cite

@inproceedings{li2023divide,
  title={Divide \& bind your attention for improved generative semantic nursing},
  author={Li, Yumeng and Keuper, Margret and Zhang, Dan and Khoreva, Anna},
  booktitle={34th British Machine Vision Conference 2023, {BMVC} 2023},
  year={2023}
}

License

This project is open-sourced under the AGPL-3.0 license. See the LICENSE file for details.

For a list of other open source components included in this project, see the file 3rd-party-licenses.txt.

Purpose of the project

This software is a research prototype, solely developed for and published as part of the publication cited above. It will neither be maintained nor monitored in any way.

Contact

Please feel free to open an issue or contact personally if you have questions, need help, or need explanations. Don't hesitate to write an email to the following email address: liyumeng07@outlook.com