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---
license: apache-2.0
task_categories:
- image-to-text
language:
- en
tags:
- multi-modal image quality assessment
pretty_name: Data-DeQA-Score
size_categories:
- 10K<n<100K
---

# Data-DeQA-Score

Datasets of the DeQA-Score paper 
(
[project page](https://depictqa.github.io/deqa-score/) / 
[codes](https://github.com/zhiyuanyou/DeQA-Score) / 
[paper](https://arxiv.org/abs/2501.11561) 
) 
in our [DepictQA project](https://depictqa.github.io/).

## Dataset Construction

- Download our meta files in this repo. 

- Download source images from [KonIQ](https://database.mmsp-kn.de/koniq-10k-database.html), 
[SPAQ](https://github.com/h4nwei/SPAQ), 
[KADID](https://database.mmsp-kn.de/kadid-10k-database.html), 
[PIPAL](https://github.com/HaomingCai/PIPAL-dataset), 
[LIVE-Wild](https://live.ece.utexas.edu/research/ChallengeDB/index.html), 
[AGIQA](https://github.com/lcysyzxdxc/AGIQA-3k-Database), 
[TID2013](https://www.ponomarenko.info/tid2013.htm), 
and [CSIQ](https://s2.smu.edu/~eclarson/csiq.html).

- Arrange the folders as follows:

```
|-- Data-DeQA-Score
  |-- KONIQ
    |-- images/*.jpg
    |-- metas
  |-- SPAQ
    |-- images/*.jpg
    |-- metas
  |-- KADID10K
    |-- images/*.png
    |-- metas
  |-- PIPAL
    |-- images/Distortion_*/*.bmp
    |-- metas
  |-- LIVE-WILD
    |-- images/*.bmp
    |-- metas
  |-- AGIQA3K
    |-- images/*.jpg
    |-- metas
  |-- TID2013
    |-- images/distorted_images/*.bmp
    |-- metas
  |-- CSIQ
    |-- images/dst_imgs/*/*.png
    |-- metas
```

If you find our work useful for your research and applications, please cite using the BibTeX:

```bibtex
@inproceedings{deqa_score,
  title={Teaching Large Language Models to Regress Accurate Image Quality Scores using Score Distribution},
  author={You, Zhiyuan and Cai, Xin and Gu, Jinjin and Xue, Tianfan and Dong, Chao},
  booktitle={IEEE Conference on Computer Vision and Pattern Recognition},
  year={2025},
}
```