Presentation

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Practical Error Estimation for Denoised Monte Carlo Image Synthesis
SessionRendering, Denoising & Path Guiding
DescriptionWe present a practical error estimation technique for denoised Monte Carlo ray tracing, using aggregated estimates of bias and variance to determine the pixel’s squared error distribution. This leads to a novel stopping criterion for denoised Monte Carlo image synthesis, that efficiently terminates rendering once a specified error is achieved.
Authors
Arthur Firmino
Luxion
Technical University of Denmark
Ravi Ramamoorthi
University of California San Diego
Jeppe Revall Frisvad
Technical University of Denmark
Henrik Wann Jensen
Luxion
Event Type
Technical Paper
TimeWednesday, 31 July 20243:45pm - 3:55pm MDT
LocationMile High 1
ACM Digital Library Journal Papers' PDFs
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Session Time & Location
Sunday, 28 July 20246:00pm - 8:45pm MDTBluebird Ballroom
Wednesday, 31 July 20243:45pm - 5:35pm MDTMile High 1
Interest Areas
Research & Education
Recordings
Livestreamed
Recorded
Keywords
Rendering
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