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Datasets:
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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 Community
2
Dataset Viewer (First 5GB)
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Search is not available for this dataset
The dataset viewer is not available for this split.
Cannot load the dataset split (in streaming mode) to extract the first rows.
Error code:   StreamingRowsError
Exception:    CastError
Message:      Couldn't cast
image: string
label: string
to
{'image': Image(mode=None, decode=True, id=None)}
because column names don't match
Traceback:    Traceback (most recent call last):
                File "/src/services/worker/src/worker/utils.py", line 99, in get_rows_or_raise
                  return get_rows(
                File "/src/libs/libcommon/src/libcommon/utils.py", line 272, in decorator
                  return func(*args, **kwargs)
                File "/src/services/worker/src/worker/utils.py", line 77, in get_rows
                  rows_plus_one = list(itertools.islice(ds, rows_max_number + 1))
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/iterable_dataset.py", line 2285, in __iter__
                  for key, example in ex_iterable:
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/iterable_dataset.py", line 1856, in __iter__
                  for key, pa_table in self._iter_arrow():
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/iterable_dataset.py", line 1888, in _iter_arrow
                  pa_table = cast_table_to_features(pa_table, self.features)
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/table.py", line 2215, in cast_table_to_features
                  raise CastError(
              datasets.table.CastError: Couldn't cast
              image: string
              label: string
              to
              {'image': Image(mode=None, decode=True, id=None)}
              because column names don't match

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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.ξˆ†

Dataset Structure

The dataset is organized as follows:ξˆ†

dataset/
β”œβ”€β”€ train/
β”‚   └── scene_id/
β”‚       β”œβ”€β”€ input/
β”‚       β”‚   β”œβ”€β”€ 000_000.png
β”‚       β”‚   β”œβ”€β”€ 000_045.png
β”‚       β”‚   └── ...
β”‚       └── gt/
β”‚           β”œβ”€β”€ 000_000.png
β”‚           β”œβ”€β”€ 000_045.png
β”‚           └── ...
β”œβ”€β”€ test/
β”‚   └── scene_id/
β”‚       β”œβ”€β”€ input/
β”‚       β”‚   β”œβ”€β”€ 000_000.png
β”‚       β”‚   β”œβ”€β”€ 000_045.png
β”‚       β”‚   └── ...
β”‚       └── gt/
β”‚           β”œβ”€β”€ 000_000.png
β”‚           β”œβ”€β”€ 000_045.png
β”‚           └── ...
  • 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.
{
  "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 [email protected].

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:ξˆ†

@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:

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