IQA-PyTorch-Weights

Model Description

This repo contains model weights used in IQA-PyTorch, a collection of Image Quality Assessment algorithms implemented in PyTorch.

Overview

The weights provided here support various IQA models and metrics, enabling assessment of both full-reference and no-reference image quality evaluation tasks.

Model Weights

The weights included in this repository come from two sources:

1. Models trained and validated by our team
2. Official weights collected from original model repositories

Usage

Please refer to the IQA-PyTorch documentation for detailed instructions on how to use these weights with the corresponding models.

Disclaimer

• Part of the weights are trained by us, while others are collected from official repositories
• While we strive for accuracy, performance is not guaranteed to exactly match original paper results
• Users should verify model performance for their specific use cases
• Please respect the original licenses and cite the appropriate papers when using these weights

Citation

If you use these weights in your research, please cite our repository and the original papers for the respective models.

@misc{pyiqa,
  title={{IQA-PyTorch}: PyTorch Toolbox for Image Quality Assessment},
  author={Chaofeng Chen and Jiadi Mo},
  year={2022},
  howpublished = "[Online]. Available: \url{https://github.com/chaofengc/IQA-PyTorch}"
}