---
license: mit
language:
- en
pretty_name: BounceBRDF
size_categories:
- n<1K
viewer: false
---
# BounceBRDF Demo Dataset

Demo dataset for the paper **"High-Gloss SVBRDF Capture Using Bounce Light"** (Eurographics 2026 / *Computer Graphics Forum*, Vol. 45, No. 2).

**Authors:** [Tomáš Iser](https://tomasiser.com), [Andrei-Timotei Ardelean](https://reality.tf.fau.de/staff/t.ardelean.html), [Tim Weyrich](https://reality.tf.fau.de/weyrich.html) — Friedrich-Alexander-Universität Erlangen-Nürnberg & Charles University

📄 [Project page & paper](https://reality.tf.fau.de/publications/2026/iser2026highgloss/iser2026highgloss.html) &nbsp;·&nbsp; 💻 [GitHub Source Code (BounceBRDF)](https://github.com/fau-vce/BounceBRDF)

## Contents

Four captured scenes (`arch1`, `re2`, `vr1`, `vr3`), each containing:

```
<scene>/
├── IMG_XXXX.exr            # RAW input photos (with mirror sphere) in EXR format
├── IMG_XXXX.envmap.exr     # Extracted environment map for each photo (using extract_envmap.py)
└── results/                # Results obtained from a subset of 9 input photos & 1000 iterations
    ├── basecolor.png       # Base color texture
    ├── roughness.png       # Roughness texture
    ├── metallic.png        # Metallic texture
    └── normal.png          # Normal map
```

The input photos and environment maps are in an [EXR](https://openexr.com/) (.exr) image format, which is an open standard for storing camera captures with high dynamic range.
The EXR images were exported from the camera RAW files using [darktable](https://www.darktable.org/).
The environment maps were extracted from the mirror sphere using our `extract_envmap.py` script.
The four `results/` textures are the SVBRDF output of our `fit.py` script.
See the [source code on GitHub](https://github.com/fau-vce/BounceBRDF).

## Usage

To reproduce the results or run the pipeline on your own data, see our [BounceBRDF repository](https://github.com/fau-vce/BounceBRDF). The extracted environment maps are already provided, so you can skip the `extract_envmap` step and run `fit` directly:

```bash
python -m bouncebrdf.fit '<scene>/*.exr'
```

## Citation

```bibtex
@article{iser2026highgloss,
  author    = {Iser, Tom\'{a}\v{s} and Ardelean, Andrei-Timotei and Weyrich, Tim},
  title     = {High-Gloss {SVBRDF} Capture Using Bounce Light},
  journal   = {Computer Graphics Forum (Proc. Eurographics)},
  volume    = {45},
  number    = {2},
  year      = {2026},
  month     = may,
  publisher = {Eurographics Association},
  authorurl = {https://reality.tf.fau.de/pub/iser2026highgloss.html},
}
```