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dc.contributor.authorCrassin, Cyrilen_US
dc.contributor.authorWyman, Chrisen_US
dc.contributor.authorMcGuire, Morganen_US
dc.contributor.authorLefohn, Aaronen_US
dc.contributor.editorPatney, Anjul and Niessner, Matthiasen_US
dc.date.accessioned2018-11-11T10:45:54Z
dc.date.available2018-11-11T10:45:54Z
dc.date.issued2018
dc.identifier.isbn978-1-4503-5896-5
dc.identifier.issn2079-8679
dc.identifier.urihttps://doi.org/10.1145/3231578.3231584
dc.identifier.urihttps://diglib.eg.org:443/handle/10.1145/3231578-3231584
dc.description.abstractGeometric 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.en_US
dc.publisherACMen_US
dc.subjectComputing methodologies
dc.subjectVisibility
dc.subjectRasterization
dc.subjectVisibility
dc.subjectFiltering
dc.subjectAntialiasing
dc.titleCorrelation-Aware Semi-Analytic Visibility for Antialiased Renderingen_US
dc.description.seriesinformationEurographics/ ACM SIGGRAPH Symposium on High Performance Graphics
dc.description.sectionheadersAnti Aliasing
dc.identifier.doi10.1145/3231578.3231584


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