| --- |
| 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) · 💻 [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}, |
| } |
| ``` |