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Datasets:
noakraicer
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Guided-Lensless-Polarization-Imaging-stageI

Tasks:
Image-to-Image
ArXiv:
Tags:
lensless
polarization
computational-imaging
guided-reconstruction
License:
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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:    UnidentifiedImageError
Message:      cannot identify image file <_io.BytesIO object at 0x7f1fe6661080>
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 "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 2690, in __iter__
                  for key, example in ex_iterable:
                                      ^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 2240, in __iter__
                  example = _apply_feature_types_on_example(
                            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 2159, in _apply_feature_types_on_example
                  decoded_example = features.decode_example(encoded_example, token_per_repo_id=token_per_repo_id)
                                    ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/features/features.py", line 2204, in decode_example
                  column_name: decode_nested_example(feature, value, token_per_repo_id=token_per_repo_id)
                               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/features/features.py", line 1508, in decode_nested_example
                  return schema.decode_example(obj, token_per_repo_id=token_per_repo_id) if obj is not None else None
                         ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/features/image.py", line 190, in decode_example
                  image = PIL.Image.open(bytes_)
                          ^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/PIL/Image.py", line 3498, in open
                  raise UnidentifiedImageError(msg)
              PIL.UnidentifiedImageError: cannot identify image file <_io.BytesIO object at 0x7f1fe6661080>

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Stage I reconstructions for evaluation (UPLight & ZJU-RGB-P)

This dataset accompanies Guided Lensless Polarization Imaging (CVPR 2026 Findings). It provides FISTA Stage-I outputs, RGB guidance images, and ground-truth polarization stacks for two public evaluation sets used in the paper.

arXiv Project Page GitHub HuggingFace Models

Layout

UPLight (~1,991 scenes)

Folder Description
UPLight/fista_grayscale/ 3-channel grayscale polarization FISTA reconstructions
UPLight/fista_color/ 12-channel RGB×4-angle FISTA reconstructions
UPLight/rgb_guide/ RGB guidance (equivalent unpolarized intensity)
UPLight/gt_grayscale/ Grayscale polarization GT
UPLight/gt_color/ Color polarization GT

ZJU-RGB-P (train / val splits)

Folder Description
ZJU-RGB-P/fista_grayscale/ train_reco_grayscale/, val_grayscale_val/
ZJU-RGB-P/fista_color/ train_after_reco/, val_after_reco/
ZJU-RGB-P/rgb_guide/ train_avg_rgb/, val_avg_rgb/
ZJU-RGB-P/gt_grayscale/ train_pol_gray/, val_gt_pol_gray/
ZJU-RGB-P/gt_color/ train_gt_pol_color/, val_gt_pol_color/

Original datasets

If you use this data, please cite our paper and the original works the evaluation sets are derived from:

  • UPLight (1,991 samples) — Liu et al., ShareCMP: Polarization-aware RGB-P semantic segmentation, IEEE TCSVT, 2025. doi:10.1109/TCSVT.2025.3570764
  • ZJU-RGB-P (394 samples) — Xiang et al., Polarization-driven semantic segmentation via efficient attention-bridged fusion, Optics Express 29(4), 4802--4820, 2021. doi:10.1364/OE.416130
BibTeX (original sources) 
@article{xiang2021polarization,
  title     = {Polarization-driven semantic segmentation via efficient attention-bridged fusion},
  author    = {Xiang, Kaite and Yang, Kailun and Wang, Kaiwei},
  journal   = {Optics Express},
  volume    = {29},
  number    = {4},
  pages     = {4802--4820},
  year      = {2021},
  publisher = {Optical Society of America}
}

@article{liu2025sharecmp,
  title   = {{ShareCMP}: Polarization-aware {RGB}-{P} semantic segmentation},
  author  = {Liu, Zhuoyan and Wang, Bo and Wang, Lizhi and Mao, Chenyu and Li, Ye},
  journal = {IEEE Transactions on Circuits and Systems for Video Technology},
  year    = {2025}
}

Citation 

@misc{kraicer2026guidedlenslesspolarizationimaging,
  title         = {Guided Lensless Polarization Imaging},
  author        = {Noa Kraicer and Erez Yosef and Raja Giryes},
  year          = {2026},
  eprint        = {2603.27357},
  archivePrefix = {arXiv},
  primaryClass  = {eess.IV},
  url           = {https://arxiv.org/abs/2603.27357}
}
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