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controlledmixturesampling's Introduction

Revisiting Controlled Mixture Sampling for Rendering Applications

teaser

A reference implementaion of the paper "Revisiting Controlled Mixture Sampling for Rendering Applications" by Qingqin Hua, Pascal Grittmann and Philipp Slusallek, SIGGRAPH 2023.

The implementaion contains our path tracing application (Section 6 and 7): Control variate formulate with per-light sampling technique and Bsdf sampling technique in global illumination.

Dependencies

The project is based on SeeSharp v1.9.0 and .NET 7.0

Running

Simply run

cd ControlledMixtureSampling
dotnet run -c Release

The code generates both equal-Spp results and equal-time results for our per-light path tracing results. You can view the results under ControlledMixtureSampling\bin\Release\net7.0\Results\PT.

We tested our code on Windows (Visual Studio 2022 Win64). It should be runnable on x86-64 Windows, Linux, and macOS by easily run the same commands above. Please follow SeeSharp for detailed compliation instructions.

Example Results

MakeFigures provides two python scripts to generate figures.

  • MakeFigures\MakeFigure8.py generates Fig. 8 in the paper.
  • MakeFigures\MakeSupplemental.py generates supplemental for different spatial grid resolutions. You can also download the supplemental here.

Below shows an equal-time result of ours in the setting of different grid resolution in full GI.

subdivision

Media

Fast Forward Video

FastForward.mov

Slides

Presentation in Mandrain with slides in English

controlledmixturesampling's People

Contributors

qingqhua avatar pgrit avatar

Stargazers

Priyansh Jalan avatar Adrien Gruson avatar Juan Raul Padron Griffe avatar  avatar Dongyu Yan avatar Qianyue He avatar Lin Hsu avatar YiChenCityU avatar  avatar  avatar Yudian Zheng avatar Zhimin Fan avatar congee.zz avatar  avatar Tianyu Li avatar  avatar Wenbo Chen avatar Ömercan Yazici avatar

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