World-Space Spatiotemporal Path Resampling for Path Tracing
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Date
2023
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Publisher
The Eurographics Association and John Wiley & Sons Ltd.
Abstract
With the advent of hardware-accelerated ray tracing, more and more real-time rendering applications tend to render images with ray-traced global illumination (GI). However, the low sample counts at real-time framerates bring enormous challenges to existing path sampling methods. Recent work (ReSTIR GI) samples indirect illumination effectively with a dramatic bias reduction. However, as a screen-space based path resampling approach, it can only reuse the path at the first bounce and brings subtle benefits for complex scenes. To this end, we propose a world-space based spatiotemporal path resampling approach. Our approach caches more path samples into a world-space grid, which allows reusing sub-path starting from non-primary path vertices. Furthermore, we introduce a practical normal-aware hash grid construction approach, providing more efficient candidate samples for path resampling. Eventually, our method achieves improvements ranging from 16.6% to 41.9% in terms of mean squared errors (MSE) compared against the previous method with only 4.4% ~ 8.4% extra time cost.
Description
CCS Concepts: Computing methodologies -> Rendering; Ray tracing
@article{10.1111:cgf.14974,
journal = {Computer Graphics Forum},
title = {{World-Space Spatiotemporal Path Resampling for Path Tracing}},
author = {Zhang, Hangyu and Wang, Beibei},
year = {2023},
publisher = {The Eurographics Association and John Wiley & Sons Ltd.},
ISSN = {1467-8659},
DOI = {10.1111/cgf.14974}
}