Code for the paper "IQA-Adapter: Exploring Knowledge Transfer from Image Quality Assessment to Diffusion-based Generative Models"
TLDR: IQA-Adapter is a tool that combines Image Quality/Aesthetics Assessment (IQA/IAA) models with image-generation and enables quality-aware generation with diffusion-based models. It allows to condition image generators on target quality/aesthetics scores.
IQA-Adapter is based on IP-Adapter architecture.
TODO list:
- Release code for IQA-Adapter inference and training for SDXL base model
- Release weights for IQA-Adapters trained with different IQA/IAA models
- Create project page
- Release code for experiments
Demonstration of guidance on quality (y-axis) and aesthetics (x-axis) scores:
If you find this work useful for your research, please cite us as follows:
@misc{iqaadapter,
title={IQA-Adapter: Exploring Knowledge Transfer from Image Quality Assessment to Diffusion-based Generative Models},
author={Khaled Abud and Sergey Lavrushkin and Alexey Kirillov and Dmitriy Vatolin},
year={2024},
eprint={2412.01794},
archivePrefix={arXiv},
primaryClass={cs.CV},
url={https://arxiv.org/abs/2412.01794},
}