Evaluating Low-Light Image Enhancement Across Multiple Intensity Levels
Paper • 2511.15496 • Published
Dataset Viewer
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: ValueError
Message: Invalid string class label MILL@761a8e0320fa8e818e5929e0cba269015cd60e06
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 2157, in _apply_feature_types_on_example
encoded_example = features.encode_example(example)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/features/features.py", line 2152, in encode_example
return encode_nested_example(self, example)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/features/features.py", line 1437, in encode_nested_example
{k: encode_nested_example(schema[k], obj.get(k), level=level + 1) for k in schema}
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/features/features.py", line 1460, in encode_nested_example
return schema.encode_example(obj) if obj is not None else None
^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/features/features.py", line 1143, in encode_example
example_data = self.str2int(example_data)
^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/features/features.py", line 1080, in str2int
output = [self._strval2int(value) for value in values]
^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/features/features.py", line 1101, in _strval2int
raise ValueError(f"Invalid string class label {value}")
ValueError: Invalid string class label MILL@761a8e0320fa8e818e5929e0cba269015cd60e06Need help to make the dataset viewer work? Make sure to review how to configure the dataset viewer, and open a discussion for direct support.
Evaluating Low-Light Image Enhancement Across Multiple Intensity Levels
CVPR Findings 2026
Project Page - Arxiv - Code
MILL Dataset
The MILL dataset can be downloaded from this repository or directly from the following links.
| Split | Camera | Resolution | Download Link |
|---|---|---|---|
| MILLs-DSLR | Nikon D5200 | 600x400 | Link (196MB) |
| MILLs-smartphone | Samsung Galaxy S7 | 600x400 | Link (227MB) |
| MILLf-DSLR | Nikon D5200 | 2012x1340 | Link (8.4GB) |
| MILLf-smartphone | Samsung Galaxy S7 | 1560x1040 | Link (915MB) |
The MILLs splits are the low-resolution splits of the MILL dataset, while the MILLf are the high-resolution ones.
MILL-Small
Both MILLs images are resized to 600x400 and follow the following data structure:
MILLs-{split}
|- 📁 train
| |- 📁 input
| | |- 🖼️ Scene1_a-1.png
| | |- 🖼️ Scene1_a-2.png
| | | ...
| | |- 🖼️ Scene1_a-10.png
| | |- 🖼️ Scene1_b-1.png
| | |- 🖼️ Scene2_a-7.png
| | |- 🖼️ Scene9-4.png
| |
| |- 📁 gt
| |- 🖼️ Scene1_a.png
| |- 🖼️ Scene1_b.png
| |- 🖼️ Scene2_a.png
| |- 🖼️ Scene9.png
|
|- 📁 validation
| ...
|- 📁 test
...
The first part of the filename defines the scene name while the second part of the input filenames defines the intensity level (from 1 to 10).
MILLf-DSLR
The full resolution DSLR split crops the 6036x4020 original images into 9 2012x1340 images. The filenames have the grid position (row-column id) in between the scene name and intensity level.
MILLf-DSLR
|- 📁 train
| |- 📁 input
| | |- 🖼️ Scene1_a-00-1.png
| | |- 🖼️ Scene1_a-01-1.png
| | | ...
| | |- 🖼️ Scene1_a-22-1.png
| | |- 🖼️ Scene1_a-00-2.png
| | | ...
| | |- 🖼️ Scene1_a-00-10.png
| | |- 🖼️ Scene1_b-22-1.png
| | |- 🖼️ Scene2_a-12-7.png
| | |- 🖼️ Scene9-02-4.png
| |
| |- 📁 gt
| |- 🖼️ Scene1_a-00.png
| |- 🖼️ Scene1_a-01.png
| |- 🖼️ Scene1_a-22.png
| |- 🖼️ Scene1_b-22.png
| |- 🖼️ Scene2_a-12.png
| |- 🖼️ Scene9-02.png
|
|- 📁 validation
| ...
|- 📁 test
...
MILLf-smartphone
It follows the same structure as the MILLs splits. The images are the original ones captured by the Samsung Galaxy S7 device.
Results
We benchmark several state-of-the-art low-light enhancement methods on the MILL dataset and reveal significant performance variations across different intensity levels. Our proposed improvements achieve up to 10 dB PSNR improvement for DSLR and 2 dB for smartphone images on Full HD resolution. For detailed results, please refer to our paper.
Citation
If you use the MILL dataset or our methods in your research, please cite our paper:
@inproceedings{pilligua2026mill,
title={MILL: Evaluating Low-Light Image Enhancement Across Multiple Intensity Levels},
author={Pilligua, Maria and Serrano-Lozano, David and Peng, Pai and Baldrich, Ramon and Brown, Michael S. and Vazquez-Corral, Javier},
booktitle={CVPR Findings},
year={2026}
}
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