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Stochastic Rendering & Visibility
Tuesday, 9 August 10:45 am - 12:15 pm | East Building, Ballroom A/B
Session Chair: Elmar Eisemann, École d'Ingénieurs Télécom ParisTech
High-Quality Spatio-Temporal Rendering Using Semi-Analytical Visibility
This paper presents:
• A novel spatio-temporal anti-aliasing algorithm with essentially noise-free results. Visibility is solved for along line samples in screen space and in time.
• A new method for ambient occlusion based on line samples/ The method can also handle motion-blurred ambient occlusion.
Carl Johan Gribel
Lund University
Rasmus Barringer
Lund University
Tomas Akenine-Möller
Lund University and Intel Corporation
Frequency Analysis and Sheared Filtering for Shadow Light Fields of Complex Occluders
A new frequency analysis and sheared filter for computing shadows cast by complex occluders. The approach uses ray tracing to sparsely sample the scene and a sheared 4D filter to share shadow samples between neighboring pixels.
Kevin Egan
Columbia University
Florian Hecht
University of California, Berkeley
Frédo Durand
MIT CSAIL
Ravi Ramamoorthi
University of California, Berkeley
Temporal Light Field Reconstruction for Rendering Distribution Effects
In this paper, a method for reconstructing high-quality images from sparse stochastic samples is applied to simultaneous motion blur, depth of field, and soft shadows.
Jaakko Lehtinen
NVIDIA Research
Timo Aila
NVIDIA Research
Jiawen Chen
MIT CSAIL
Samuli Laine
NVIDIA Research
Frédo Durand
MIT CSAIL
The Area Perspective Transform: A Homogeneous Transform for Efficient In-Volume Queries
This paper introduces a homogeneous transform that reduces the computation required to determine the set of points or primitives inside a tetrahedral volume. It describes how application of this transform can improve the efficiency of soft shadows and defocus blur computations.
Warren Hunt
Intel Corporation
Gregory Johnson
University of Texas at Austin and Intel Corporation
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