Below are the existing IQA databases used for the assessment (A3) task in the Q-Bench.
| Database | Json file | Download link |
|---|---|---|
| In-the-wild: KONiQ-10k | koniq.json | KONiQ-10k |
| In-the-wild: SPAQ | spaq.json | SPAQ |
| In-the-wild: LIVE-FB | flive.json | LIVE-FB |
| In-the-wild: LIVE-itw | livec.json | LIVE-itw |
| Generated: CGIQA-6K | cgi.json | CGIQA-6K |
| Generated: AGIQA-3K | agi.json | AGIQA-3K |
| Artificial: KADID-10K | kadid.json | KADID-10K |
Please contact any of the first authors of this paper for queries.
- Haoning Wu,
haoning001@e.ntu.edu.sg - Zicheng Zhang,
zzc1998@sjtu.edu.cn - Erli Zhang,
ezhang005@e.ntu.edu.sg
If you find our work interesting, please feel free to cite our paper:
@article{wu2023qbench,
title={Q-Bench: A Benchmark for General-Purpose Foundation Models on Low-level Vision},
author={Wu, Haoning and Zhang, Zicheng and Zhang, Erli and Chen, Chaofeng and Liao, Liang and Wang, Annan and Li, Chunyi and Sun, Wenxiu and Yan, Qiong and Zhai, Guangtao and Lin, Weisi},
year={2023},
}