S2R-HDR: A Large-Scale Rendered Dataset for HDR Fusion
Paper
• 2504.07667 • Published
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The dataset generation failed
Error code: DatasetGenerationError
Exception: ArrowInvalid
Message: JSON parse error: The document is empty.
Traceback: Traceback (most recent call last):
File "/usr/local/lib/python3.12/site-packages/datasets/packaged_modules/json/json.py", line 183, in _generate_tables
df = pandas_read_json(f)
^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/packaged_modules/json/json.py", line 38, in pandas_read_json
return pd.read_json(path_or_buf, **kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/pandas/io/json/_json.py", line 815, in read_json
return json_reader.read()
^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/pandas/io/json/_json.py", line 1014, in read
obj = self._get_object_parser(self.data)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/pandas/io/json/_json.py", line 1040, in _get_object_parser
obj = FrameParser(json, **kwargs).parse()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/pandas/io/json/_json.py", line 1176, in parse
self._parse()
File "/usr/local/lib/python3.12/site-packages/pandas/io/json/_json.py", line 1392, in _parse
ujson_loads(json, precise_float=self.precise_float), dtype=None
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
ValueError: Expected object or value
During handling of the above exception, another exception occurred:
Traceback (most recent call last):
File "/usr/local/lib/python3.12/site-packages/datasets/builder.py", line 1869, in _prepare_split_single
for key, table in generator:
^^^^^^^^^
File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 609, in wrapped
for item in generator(*args, **kwargs):
^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/packaged_modules/json/json.py", line 186, in _generate_tables
raise e
File "/usr/local/lib/python3.12/site-packages/datasets/packaged_modules/json/json.py", line 160, in _generate_tables
pa_table = paj.read_json(
^^^^^^^^^^^^^^
File "pyarrow/_json.pyx", line 342, in pyarrow._json.read_json
File "pyarrow/error.pxi", line 155, in pyarrow.lib.pyarrow_internal_check_status
File "pyarrow/error.pxi", line 92, in pyarrow.lib.check_status
pyarrow.lib.ArrowInvalid: JSON parse error: The document is empty.
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 1342, in compute_config_parquet_and_info_response
parquet_operations, partial, estimated_dataset_info = stream_convert_to_parquet(
^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 907, in stream_convert_to_parquet
builder._prepare_split(split_generator=splits_generators[split], file_format="parquet")
File "/usr/local/lib/python3.12/site-packages/datasets/builder.py", line 1736, in _prepare_split
for job_id, done, content in self._prepare_split_single(
^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/builder.py", line 1919, in _prepare_split_single
raise DatasetGenerationError("An error occurred while generating the dataset") from e
datasets.exceptions.DatasetGenerationError: An error occurred while generating the datasetNeed help to make the dataset viewer work? Make sure to review how to configure the dataset viewer, and open a discussion for direct support.
class_name string | convention string | extrinsic_r list | extrinsic_t list | height int64 | intrinsic list | name string | width int64 | world2cam bool |
|---|---|---|---|---|---|---|---|---|
PinholeCameraParameter | opencv | [
[
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[
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],
[
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] | default | 1,920 | true |
PinholeCameraParameter | opencv | [
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] | default | 1,920 | true |
PinholeCameraParameter | opencv | [
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[
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[
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] | default | 1,920 | true |
PinholeCameraParameter | opencv | [
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] | default | 1,920 | true |
PinholeCameraParameter | opencv | [
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[
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0.9995360374450684,
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] | [
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] | default | 1,920 | true |
PinholeCameraParameter | opencv | [
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] | default | 1,920 | true |
PinholeCameraParameter | opencv | [
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[
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] | default | 1,920 | true |
PinholeCameraParameter | opencv | [
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] | default | 1,920 | true |
PinholeCameraParameter | opencv | [
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0.9995298981666565,
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] | default | 1,920 | true |
PinholeCameraParameter | opencv | [
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PinholeCameraParameter | opencv | [
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PinholeCameraParameter | opencv | [
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PinholeCameraParameter | opencv | [
[
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PinholeCameraParameter | opencv | [
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PinholeCameraParameter | opencv | [
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PinholeCameraParameter | opencv | [
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PinholeCameraParameter | opencv | [
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PinholeCameraParameter | opencv | [
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PinholeCameraParameter | opencv | [
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PinholeCameraParameter | opencv | [
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PinholeCameraParameter | opencv | [
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PinholeCameraParameter | opencv | [
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PinholeCameraParameter | opencv | [
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PinholeCameraParameter | opencv | [
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End of preview.
✨Dataset Summary
S2R-HDR is a large-scale synthetic dataset for high dynamic range (HDR) reconstruction tasks. It contains 1,000 motion sequences, each comprising 24 images at 1920×1080 resolution, with a total of 24,000 images. To support flexible data augmentation, all images are stored in EXR format with linear HDR values. The dataset is rendered using Unreal Engine 5 and our custom pipeline built upon XRFeitoria, encompassing diverse dynamic elements, motion patterns, HDR-compatible scenes, and varied lighting conditions. Beyond the core imagery, we additionally provide per-frame rendered auxiliary data including optical flow, depth maps, surface normals, and diffuse albedo information, significantly expanding S2R-HDR's potential applications across various computer vision tasks.
Note: The other half of the data is stored in a separate repository: https://huggingface.co/datasets/iimmortall/S2R-HDR.
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🔔News
- 🔥 We are pleased to announce the official release of our S2R-HDR dataset. We welcome the utilization of this resource and the provision of valuable feedback for continuous improvement.
🏭Dataset Structure
# S2R-HDR
./
├── scene_0_FM
│ ├── camera_params
│ ├── img
│ │ ├── 0000.exr
│ │ ├── [...]
│ │ ├── 0023.exr
│ ├── diffuse
│ │ ├── [...]
│ ├── flow
│ │ ├── [...]
│ ├── depth
│ │ ├── [...]
│ ├── normal
│ │ ├── [...]
├── scene_1_LM_shake
├── [...]
⚠ Note: In the suffix of the sequence name, LM/FM means that the motion mode of this sequence is Local Motion/Full Motion. Shake/No Shake means whether there is simulated camera shake in this sequence.
🏆Dataset Details
Dataset Construction
We implemented three targeted technical enhancements to enhance our synthetic dataset's photorealistic quality, content diversity, and scale.
- A custom UE5 rendering pipeline was designed to preserve radiometrically linear data by disabling built-in tone mapping and gamma correction operations throughout the rendering process.
- We incorporated Perlin noise-based camera shake simulation to replicate the vibrations and instabilities inherent in physical camera systems during real-world capture scenarios.
- A comprehensive asset library was developed containing: 1) animated foreground elements (animals, pedestrians, vehicles); 2) environment sets covering both interior and exterior spaces; 3) distinct HDR lighting configurations simulating daylight, twilight, and nighttime conditions with detailed quantitative breakdowns provided as follows.
| Motion Type | Environment | Time | ||
|---|---|---|---|---|
| Daylight | Twilight | Night | ||
| Local Motion | Indoor | 2016 | 1152 | 432 |
| Outdoor | 2160 | 1440 | 1104 | |
| Full Motion | Indoor | 3360 | 1920 | 720 |
| Outdoor | 4272 | 3024 | 2400 | |
✏️Citation
@article{wang2025s2r,
title={S2R-HDR: A Large-Scale Rendered Dataset for HDR Fusion},
author={Wang, Yujin and Wu, Jiarui and Bian, Yichen and Zhang, Fan and Xue, Tianfan},
journal={arXiv preprint arXiv:2504.07667},
year={2025}
}
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