|
|
--- |
|
|
dataset_info: |
|
|
features: |
|
|
- name: id |
|
|
dtype: string |
|
|
- name: hq_img |
|
|
dtype: image |
|
|
- name: lq_img |
|
|
dtype: image |
|
|
- name: text |
|
|
sequence: string |
|
|
- name: bbox |
|
|
sequence: |
|
|
array2_d: |
|
|
shape: |
|
|
- 2 |
|
|
- 2 |
|
|
dtype: int32 |
|
|
- name: poly |
|
|
sequence: |
|
|
array2_d: |
|
|
shape: |
|
|
- 16 |
|
|
- 2 |
|
|
dtype: int32 |
|
|
splits: |
|
|
- name: test |
|
|
num_bytes: 55089874.0 |
|
|
num_examples: 847 |
|
|
download_size: 54622145 |
|
|
dataset_size: 55089874.0 |
|
|
configs: |
|
|
- config_name: default |
|
|
data_files: |
|
|
- split: test |
|
|
path: data/test-* |
|
|
language: |
|
|
- en |
|
|
size_categories: |
|
|
- 10M<n<100M |
|
|
task_categories: |
|
|
- image-to-image |
|
|
tags: |
|
|
- image-restoration |
|
|
- diffusion-models |
|
|
- text-recognition |
|
|
--- |
|
|
|
|
|
# Real-Text |
|
|
|
|
|
**Text-Aware Image Restoration with Diffusion Models** (arXiv:2506.09993) |
|
|
Real-world evaluation dataset for the TAIR task. |
|
|
|
|
|
- 📄 Paper: https://arxiv.org/abs/2506.09993 |
|
|
- 🌐 Project Page: https://cvlab-kaist.github.io/TAIR/ |
|
|
- 💻 GitHub: https://github.com/cvlab-kaist/TAIR |
|
|
- 🛠 Dataset Pipeline: https://github.com/paulcho98/text_restoration_dataset |
|
|
|
|
|
## Dataset Description |
|
|
|
|
|
**Real-Text** is an evaluation dataset constructed from [RealSR](https://github.com/csjcai/RealSR) and [DrealSR](https://github.com/xiezw5/Component-Divide-and-Conquer-for-Real-World-Image-Super-Resolution) using the same pipeline as SA-Text. It reflects **real-world degradation and distortion**, making it suitable for robust benchmarking. |
|
|
|
|
|
## Notes |
|
|
|
|
|
- This dataset is designed for testing oour model, **TeReDiff**, under realistic settings. |
|
|
- Check [SA-text](https://huggingface.co/datasets/Min-Jaewon/SA-Text) for training dataset. |
|
|
- Please refer to our [dataset pipeline](https://github.com/paulcho98/text_restoration_dataset). |
|
|
|
|
|
## Citation |
|
|
|
|
|
Please cite the following paper if you use this dataset: |
|
|
``` |
|
|
{ |
|
|
@article{min2024textaware, |
|
|
title={Text-Aware Image Restoration with Diffusion Models}, |
|
|
author={Min, Jaewon and Kim, Jin Hyeon and Cho, Paul Hyunbin and Lee, Jaeeun and Park, Jihye and Park, Minkyu and Kim, Sangpil and Park, Hyunhee and Kim, Seungryong}, |
|
|
journal={arXiv preprint arXiv:2506.09993}, |
|
|
year={2025} |
|
|
} |
|
|
``` |
