“Dynamic Diffuse Global Illumination Resampling” by Majercik, Mueller, Keller, Nowrouzezahrai and McGuire
Conference:
Type(s):
Interest Area:
- Gaming & Interactive, Research / Education, AI / Machine Learning, Rendering, and Scientific Visualization
Title:
- Dynamic Diffuse Global Illumination Resampling
Session/Category Title: Real-Time Rendering
Presenter(s)/Author(s):
Abstract:
Ray traced global illumination can be partitioned into direct contributions of the light sources that reflect to the camera after one bounce and indirect contributions that scatter for multiple bounces. We propose a new real-time solution called dynamic diffuse global illumination resampling that computes direct and indirect illumination accurately and with low noise. The key idea is to derive a new, unified algorithm from the principles of the state of the art ReSTIR many-lights direct shadowing [Bitterli et al. 2020] and the DDGI indirect light probes [Majercik et al. 2019] real-time algorithms. By this unification, global illumination resampling achieves higher quality than the combination of its two components at real-time framerates. At the cost of little bias, our technique also outperforms hardware accelerated path tracing in both runtime and noise.
References:
[1]
Benedikt Bitterli, Chris Wyman, Matt Pharr, Peter Shirley, Aaron Lefohn, and Wojciech Jarosz. 2020. Spatiotemporal Reservoir Resampling for Real-time Ray Tracing with Dynamic Direct Lighting. ACM Transactions on Graphics (Proceedings of SIGGRAPH) 39, 4, Article 148 (July 2020), 17 pages.
[2]
Thomas Kollig and Alexander Keller. 2004. Illumination in the Presence of Weak Singularities. In Monte Carlo and Quasi-Monte Carlo Methods 2004, Denis Talayand Harald Niederreiter (Eds.). Springer, 245–257.
[3]
Zander Majercik, Jean-Philippe Guertin, Derek Nowrouzezahrai, and Morgan McGuire. 2019. Dynamic Diffuse Global Illumination with Ray-Traced Irradiance Fields. Journal of Computer Graphics Techniques (JCGT) 8, 2 (5 June 2019), 1–30.
[4]
Eric Veach and Leonidas J. Guibas. 1995. Optimally Combining Sampling Techniques for Monte Carlo Rendering. In Proceedings of the 22nd Annual Conference on Computer Graphics and Interactive Techniques(SIGGRAPH ’95). 419–428.
[5]
Jiří Vorba, Johannes Hanika, Sebastian Herholz, Thomas Müller, Jaroslav Křivánek, and Alexander Keller. 2019. Path Guiding in Production. In ACM SIGGRAPH 2019 Courses(SIGGRAPH ’19). Article 18, 77 pages.
