Correlation-Aware Semi-Analytic Visibility for Antialiased Rendering
Cyril Crassin ; Chris Wyman ; Morgan McGuire ; Aaron LefohnHPG ’18: High-Performance Graphics (inproceedings)
Abstract
Geometric aliasing is a persistent challenge for real-time rendering. Hardware multisampling remains limited to 8 × , analytic coverage fails to capture correlated visibility samples, and spatial and temporal postfiltering primarily target edges of superpixel primitives. We describe a novel semi-analytic representation of coverage designed to make progress on geometric antialiasing for subpixel primitives and pixels containing many edges while handling correlated subpixel coverage. Although not yet fast enough to deploy, it crosses three critical thresholds: image quality comparable to 256× MSAA, faster than 64× MSAA, and constant space per pixel.
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BibTex references
@inproceedings{CWML18,
author = {Cyril Crassin and Chris Wyman and Morgan McGuire and Aaron Lefohn},
title = {Correlation-Aware Semi-Analytic Visibility for Antialiased Rendering},
url = {https://research.nvidia.com/sites/default/files/pubs/2018-08_Correlation-Aware-Semi-Analytic-Visibility//CorrelationAwareVisibility_AuthorsVersion.pdf, Paper - Authors Version},
year = {2018},
date = {2018-08-10},
booktitle = {HPG ’18: High-Performance Graphics},
}
author = {Cyril Crassin and Chris Wyman and Morgan McGuire and Aaron Lefohn},
title = {Correlation-Aware Semi-Analytic Visibility for Antialiased Rendering},
url = {https://research.nvidia.com/sites/default/files/pubs/2018-08_Correlation-Aware-Semi-Analytic-Visibility//CorrelationAwareVisibility_AuthorsVersion.pdf, Paper - Authors Version},
year = {2018},
date = {2018-08-10},
booktitle = {HPG ’18: High-Performance Graphics},
}