iBRDF

This is the code for the paper "Invertible Neural BRDF for Object Inverse Rendering".

Prerequisites

1. A C++ 17-compatible compiler
2. CUDA 10.2
3. CMake
4. LibTorch 1.6.0
5. OptiX 7.0.0
6. TinyEXR (bundled)

Usage

A Dockerfile is provided to help setup the environment. The following commands are assumed to be run inside the Docker container, though it is not a necessity.

Building

Download and extract LibTorch and OptiX into ./third_party/libtorch and ./third_party/optix respectively. Then run the following commands to build the project:

mkdir build
cd build
cmake ..
make

Training iBRDF

Assuming that MERL BRDF binaries are placed inside the ../datasets/merl folder. Run the following command to pre-process them into a format that is suitable for training:

python ./scripts/preprocess_merl.py ../datasets/merl ../datasets/merl_processed

The resulting BRDFs will be placed under ../datasets/merl_processed. After conversion, run the following command to train iBRDF:

Usage: ./build/bin/ibrdf_train [MERL root] [Number of BRDFs per batch] [Number of samples per BRDF] [Number of epochs] [Output]

Example: ./build/bin/ibrdf_train ../datasets/merl_processed 50 10000 10000 ./run/ibrdf

Material Estimation

Usage: ./build/bin/estbrdf [Input] [Geometry] [Illumination] [iBRDF model] [Number of lobes] [Number of optimization steps] [Output]

Example: ./build/bin/estbrdf ./run/render.exr ./data/sphere.pt ./data/uffizi-large.exr ./data/ibrdf.pt 2 200 ./run/brdf.binary

Illumination Estimation

Usage: ./build/bin/estillu [Input] [Geometry] [Material] [Mirror reflection] [Illumination width] [Illumination height] [Output]

Example: ./build/bin/estillu ./run/a.exr ./data/sphere.pt ./data/alum-bronze.binary 0 512 256 2000 ./run/illu.exr

Joint Estimation of Illumination and Material

Usage: ./build/bin/estboth [Input] [Geometry] [iBRDF model] [Number of lobes] [Illumination width] [Illumination height] [Number of optimization steps] [Number of material optimization steps] [Number of illumination optimization steps] [Number of gray world steps] [Output material] [Output illumination]

Example: ./build/bin/estboth ./run/render.exr ./data/sphere.pt ./data/ibrdf.pt 2 256 128 10 100 300 3 ./run/brdf.binary ./run/illu.exr

Rendering

Usage: ./build/bin/render [Geometry] [Material] [Illumination] [Mirror reflection] [Output]

Example: ./build/bin/render ./data/sphere.pt ./data/alum-bronze.binary ./data/uffizi-large.exr 0 ./run/render.exr

Citation

@INPROCEEDINGS {Chen_2020_ECCV,
    author    = "Chen, Zhe and Nobuhara, Shohei and Nishino, Ko",
    title     = "Invertible Neural BRDF for Object Inverse Rendering",
    booktitle = "Proceedings of the European Conference on Computer Vision (ECCV)",
    year      = "2020"
}

LICENSE

MIT Liencse