---
license: cc-by-nc-4.0
---
# 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](https://doi.org/10.48550/arXiv.2512.21040)].  

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|
|:-------------------------:|:-------------------------:|
|<img width="512" alt="RGB" src="rgb_1024.png">|<img width="512" alt="Depth" src="depth_1024.png">|

|Amplitude|Phase|
|:-------------------------:|:-------------------------:|
|<img width="512" alt="Amplitude" src="amplitude_1024.webp">|<img width="512" alt="Phase" src="phase_1024.webp">|

## 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             |



---
### Source 3D Models
The RGB-D scenes were generated from 3D meshes obtained from the [Google Scanned Objects](https://research.google/blog/scanned-objects-by-google-research-a-dataset-of-3d-scanned-common-household-items/
).  

---
# 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](./LICENSE.txt) and the [official CC BY-NC 4.0 license](https://creativecommons.org/licenses/by-nc/4.0/) for full terms.

For inquiries, please contact the corresponding author: **bluekdct@gmail.com**


---

## 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}, 
}
```
---