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DTSTAMP:20260114T163645Z
LOCATION:Meeting Room C4.8\, Level 4 (Convention Centre)
DTSTART;TZID=Australia/Melbourne:20231215T094000
DTEND;TZID=Australia/Melbourne:20231215T095000
UID:siggraphasia_SIGGRAPH Asia 2023_sess155_papers_744@linklings.com
SUMMARY:ExtraSS: A Framework for Joint Spatial Super Sampling and Frame Ex
 trapolation
DESCRIPTION:Songyin Wu (University of California Santa Barbara); Sungye Ki
 m (Intel Corporation); Zheng Zeng (University of California, Santa Barbara
 ); Deepak Vembar, Sangeeta Jha, and Anton Kaplanyan (Intel Corporation); a
 nd Ling-Qi Yan (University of California, Santa Barbara)\n\nWe introduce E
 xtraSS, a novel framework that combines spatial super sampling and frame e
 xtrapolation to enhance real-time rendering performance. By integrating th
 ese techniques, our approach achieves a balance between performance and qu
 ality, generating temporally stable and high-quality, high-resolution resu
 lts. Leveraging lightweight modules on warping and the ExtraSSNet for refi
 nement, we exploit spatial-temporal information, improve rendering sharpne
 ss, handle moving shadings accurately, and generate temporally stable resu
 lts. Computational costs are significantly reduced compared to traditional
  rendering methods, enabling higher frame rates and alias-free high resolu
 tion results. Evaluation using Unreal Engine demonstrates the benefits of 
 our framework over conventional individual spatial or temporal super sampl
 ing methods, delivering improved rendering speed and visual quality. With 
 its ability to generate temporally stable high-quality results, our framew
 ork creates new possibilities for real-time rendering applications, advanc
 ing the boundaries of performance and photo-realistic rendering in various
  domains.\n\nRegistration Category: Full Access\n\nSession Chair: Sing Chu
 n Lee (Bucknell University)\n\n
URL:https://asia.siggraph.org/2023/full-program?id=papers_744&sess=sess155
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