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--- |
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license: apache-2.0 |
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task_categories: |
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- image-to-text |
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language: |
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- en |
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tags: |
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- multi-modal image quality assessment |
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pretty_name: Data-DeQA-Score |
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size_categories: |
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- 10K<n<100K |
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--- |
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# Data-DeQA-Score |
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Datasets of the DeQA-Score paper |
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( |
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[project page](https://depictqa.github.io/deqa-score/) / |
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[codes](https://github.com/zhiyuanyou/DeQA-Score) / |
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[paper](https://arxiv.org/abs/2501.11561) |
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) |
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in our [DepictQA project](https://depictqa.github.io/). |
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## Dataset Construction |
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- Download our meta files in this repo. |
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- Download source images from [KonIQ](https://database.mmsp-kn.de/koniq-10k-database.html), |
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[SPAQ](https://github.com/h4nwei/SPAQ), |
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[KADID](https://database.mmsp-kn.de/kadid-10k-database.html), |
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[PIPAL](https://github.com/HaomingCai/PIPAL-dataset), |
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[LIVE-Wild](https://live.ece.utexas.edu/research/ChallengeDB/index.html), |
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[AGIQA](https://github.com/lcysyzxdxc/AGIQA-3k-Database), |
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[TID2013](https://www.ponomarenko.info/tid2013.htm), |
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and [CSIQ](https://s2.smu.edu/~eclarson/csiq.html). |
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- Arrange the folders as follows: |
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``` |
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|-- Data-DeQA-Score |
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|-- KONIQ |
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|-- images/*.jpg |
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|-- metas |
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|-- SPAQ |
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|-- images/*.jpg |
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|-- metas |
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|-- KADID10K |
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|-- images/*.png |
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|-- metas |
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|-- PIPAL |
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|-- images/Distortion_*/*.bmp |
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|-- metas |
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|-- LIVE-WILD |
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|-- images/*.bmp |
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|-- metas |
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|-- AGIQA3K |
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|-- images/*.jpg |
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|-- metas |
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|-- TID2013 |
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|-- images/distorted_images/*.bmp |
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|-- metas |
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|-- CSIQ |
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|-- images/dst_imgs/*/*.png |
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|-- metas |
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``` |
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If you find our work useful for your research and applications, please cite using the BibTeX: |
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```bibtex |
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@inproceedings{deqa_score, |
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title={Teaching Large Language Models to Regress Accurate Image Quality Scores using Score Distribution}, |
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author={You, Zhiyuan and Cai, Xin and Gu, Jinjin and Xue, Tianfan and Dong, Chao}, |
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booktitle={IEEE Conference on Computer Vision and Pattern Recognition}, |
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year={2025}, |
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} |
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``` |
