Zevin2023/SEAGULL-100w
Contents Introduction Data Structure Construction Pipeline Acknowledgement Citation Introduction This is a large-scale synthetic ROI-based IQA dataset, SEAGULL-100w, for "SEAGULL: No-reference Image Quality Assessment for Regions of Interest via Vision-Language Instruction Tuning." We create distortion (Dist.) images with six different distortion types, namely blur, sharpness, exposure, contrast, colorfulness and compression. We sample… See the full description on the dataset page: https://huggingface.co/datasets/Zevin2023/SEAGULL-100w.
| Author / organization | Zevin2023 |
|---|---|
| License (as declared) | mit |
| Downloads | 135 (as reported by Hugging Face) |
| Likes | 4 |
| Created | 18 November 2024 |
| Last updated at source | 25 November 2024 |
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