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Datasets:
JingRuan
/
PolaRGB

Tasks:
Image-to-Image
Modalities:
Image
Formats:
imagefolder
Languages:
English
Size:
1K - 10K
ArXiv:
Tags:
computer-vision
reflection-removal
polarization
image-processing
cvpr2025
Libraries:
Datasets
License:
Dataset card Data Studio Files
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1
PolaRGB
File size: 2,859 Bytes
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---
pretty_name: PolarFree
tags:
- computer-vision
- reflection-removal
- polarization
- image-processing
- cvpr2025
license: cc-by-nc-4.0
datasets:
- polarfree
language:
- en
size_categories:
- 10K<n<100K
task_categories:
- image-to-image
---

# PolarFree: Polarization-based Reflection-Free Imaging

## Dataset Overview

PolarFree is a high-quality dataset designed for polarization-based reflection removal tasks, as introduced in the CVPR 2025 paper "PolarFree: Polarization-based Reflection-Free Imaging". The dataset aims to support tasks such as image reflection removal and image enhancement, particularly suitable for training and evaluating image enhancement models.

## Dataset Structure

The dataset is organized as follows:

```
dataset/
├── train/
│   └── scene_id/
│       ├── input/
│       │   ├── 000_000.png
│       │   ├── 000_045.png
│       │   └── ...
│       └── gt/
│           ├── 000_000.png
│           ├── 000_045.png
│           └── ...
├── test/
│   └── scene_id/
│       ├── input/
│       │   ├── 000_000.png
│       │   ├── 000_045.png
│       │   └── ...
│       └── gt/
│           ├── 000_000.png
│           ├── 000_045.png
│           └── ...
```

- **input/scene_id/**: Contains multiple input images captured at different polarization angles. Each group of images shares the same prefix number (e.g., 000, 001), indicating they belong to the same set.
- **gt/scene_id/**: Contains the corresponding high-quality ground truth images used as references for the input images.

```json
{
  "inputs": [
    "input/scene_id/001_000.png",
    "input/scene_id/001_045.png",
    "input/scene_id/001_090.png",
    "input/scene_id/001_rgb.png"
  ],
  "gt": [
    "gt/scene_id/000_000.png",
    "gt/scene_id/000_045.png",
    "gt/scene_id/000_090.png",
    "gt/scene_id/000_rgb.png"
  ]
}
```

The training and testing data are all available! If you want raw images, please contact me via mingdeyao@foxmail.com.

## Supported Task

- **Image Reflection Removal**: Utilizing polarization information to remove reflections from input images, resulting in clearer images.

## Citation

If you use the PolarFree dataset in your research, please cite the following paper:

```bibtex
@inproceedings{polarfree2025,
  title={PolarFree: Polarization-based Reflection-Free Imaging},
  author={Yao, Mingde and Wang, Menglu and Tam, King-Man and Li, Lingen and Xue, Tianfan and Gu, Jinwei},
  booktitle={CVPR},
  year={2025}
}
```

For more information, please visit the project page:

- GitHub Repository: [https://github.com/mdyao/PolarFree](https://github.com/mdyao/PolarFree)
- Paper: [https://arxiv.org/abs/2503.18055](https://arxiv.org/abs/2503.18055)

---