Filtering-Based Reconstruction for Gradient-Domain Rendering

Build

Clone

Clone the repository and fetch all submodules recursively.

git clone https://github.com/lastmc/FRGR.git
cd FRGR
git submodule update --init --recursive

Requirements

OpenCV with contrib and openexr module.

For example, OpenCV could be installed through vcpkg in Windows:

vcpkg install opencv[contrib,openexr]:x64-windows

Build by CMake

cmake -S . -B build
cmake --build build

The built executable should be in folder build/bin

Run

An example run script is:

build/bin/main.exe -i color.exr --image_pt color_pt.exr -v var.exr --var_pt var_pt.exr dx.exr dy.exr -a albedo.exr -n normal.exr --albedo_var albedoVariance.exr --normal_var normalVariance.exr --lambda 0.5 -A 1 -N 0.01 -r 3 -G 1 -l 2 -s 64 -d example-scenes/kitchen --output build/test.exr

An example scene is provided in example-scenes/kitchen. The example scene is 64spp, thus the folder path is example-scenes/kitchen/64spp. The spp parameter is provided by -s.

Set the --output flag to choose where to save the output file. Also, the enhanced gradients are outputed to example-scenes/kitchen/outputs in the provided example.

Citation

To cite us, you can use the following bibtex entry.

@inproceedings{10.1145/3680528.3687568,
author = {Yan, Difei and Zheng, Shaokun and Yan, Ling-Qi and Xu, Kun},
title = {Filtering-Based Reconstruction for Gradient-Domain Rendering},
year = {2024},
isbn = {9798400711312},
publisher = {Association for Computing Machinery},
address = {New York, NY, USA},
url = {https://doi.org/10.1145/3680528.3687568},
doi = {10.1145/3680528.3687568},
booktitle = {SIGGRAPH Asia 2024 Conference Papers},
articleno = {69},
numpages = {10},
keywords = {Gradient-Domain Rendering, Reconstruction, Optimization},
series = {SA '24}
}