Sample Distribution Shadow Maps

This demo showcases an extension to Z-partitioning (cascaded shadow maps) called Sample Distribution Shadow Maps (SDSMs). SDSMs optimize the placement and size of a fixed number of Z-partitions by analyzing the shadow sample distribution required by the current frame. They build on the advantages of current state of the art techniques, including predictable performance and constant memory usage,...
Authored by Andrew Lauritzen (Intel) Last updated on 06/07/2017 - 12:23

Adaptive Volumetric Shadow Maps

We introduce adaptive volumetric shadow maps (AVSM), a real-time shadow algorithm that supports high-quality shadowing from dynamic volumetric media such as hair and smoke. The key contribution of AVSM is the introduction of a streaming simplification algorithm that generates an accurate volumetric light attenuation function using a small fixed memory footprint. This compression strategy leads to...
Authored by Last updated on 06/07/2017 - 12:25
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