SPIN-Lab/KOREATECH-CGH-1024-3.6Mu

Koreatech-CGH

This dataset consists of RGBD–complex hologram pairs designed for training machine learning–based computer-generated holography (ML-CGH) models.
It can be used for tasks such as hologram generation, hologram upscaling, and related applications.

The holograms were generated using a layer-based hologram generation method[arxiv].

Note that this dataset is licensed under the Creative Commons Attribution 4.0 International License Non Commercial (CC BY-NC 4.0).

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Dataset Sample

RGB	Depth

Amplitude	Phase

Data Details

Directory structure

root
  ├─test
  │  ├─amp
  │     └─*.exr
  │  ├─depth
  │  ├─img
  │  └─phs
  ├─train
  │  ├─amp
  │  ├─depth
  │  ├─img
  │  └─phs
  └─validation
      ├─amp
      ├─depth
      ├─img
      └─phs

Dataset Configuration

	Format	Channels	Resolution	Precision	Range
RGB	.exr	3	1024 × 1024	fp32	0-1
Depth	.exr	1	1024 × 1024	fp32	0-1
Amplitude	.exr	3	1024 × 1024	fp32	dependent to data
Phase	.exr	3	1024 × 1024	fp32	0-1

Hologram Parameters

Parameter	Value
Resolution	1024 × 1024
Pixel Pitch	3.6 μm
Wavelength (R,G,B)	638 nm, 532 nm, 450 nm
Physical Extent (H × W × D)	3.6864 mm × 3.6864 mm × 40.66723 mm

Data Splits

Split	Number of Samples
Train	5,000
Validation	500
Test	500

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Source 3D Models

The RGB-D scenes were generated from 3D meshes obtained from the Google Scanned Objects.

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License

© 2025, SPIN Lab, Korea University of Technology and Education (KOREATECH) and Digital Holography Research Group, Electronics and Telecommunications Research Institute (ETRI)
This dataset is licensed under the Creative Commons Attribution-NonCommercial 4.0 International (CC BY-NC 4.0) license.
You are free to use, modify, and distribute this work for non-commercial purposes, with proper attribution.
Commercial use is strictly prohibited.

See LICENSE and the official CC BY-NC 4.0 license for full terms.

For inquiries, please contact the corresponding author: [email protected]

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Acknowledgements

This work was supported by the National Research Foundation of Korea (NRF) through the Ministry of Education's Basic Science Research Program (Grant 2021R1I1A3048263, 50%) and by the Institute of Information and Communications Technology Planning and Evaluation (IITP) grant funded by the Korea Government (MSIT) (Grant 2019-0-00001, 50%).

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Citation

@misc{lee2025largedepthrangelayerbasedhologramdataset,
      title={A Large-Depth-Range Layer-Based Hologram Dataset for Machine Learning-Based 3D Computer-Generated Holography}, 
      author={Jaehong Lee and You Chan No and YoungWoo Kim and Duksu Kim},
      year={2025},
      eprint={2512.21040},
      archivePrefix={arXiv},
      primaryClass={cs.CV},
      url={https://arxiv.org/abs/2512.21040}, 
}

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