Subsurface scattering is an important visual cue and in real-time rendering it is often approximated using screen-space algorithms. Path tracing with the diffusion approximation can easily overcome the limitations of these algorithms, but increases image noise. We improve its efficiency by applying reservoir-based spatiotemporal importance resampling (ReSTIR) to subsurface light transport paths. For this, we adopt BSSRDF importance sampling for generating candidates. Further, spatiotemporal reuse requires shifting paths between domains. We observe that different image regions benefit most from either reconnecting through the translucent object (reconnection shift), or one vertex later (delayed reconnection shift). We first introduce a local subsurface scattering specific criterion for a hybrid shift that deterministically selects one of the two shifts for a path. Due to the locality, it cannot always choose the most efficient shift, e.g. near shadow boundaries. Therefore, we additionally propose a novel sequential shift to combine multiple shift mappings: We execute subsequent resampling passes, each one using a different shift, which does not require to deterministically choose a shift for a path. Instead, resampling can pick the most successful shift implicitly. Our method achieves realtime performance and significantly reduces noise and denoising artifacts in regions with visible subsurface scattering compared to standard path tracing with equal render time.
机构:
Tsinghua Univ, Beijing, Peoples R China
INRIA Grenoble Rhone Alpes, Grenoble, France
CNRS, F-75700 Paris, France
Univ Grenoble, Lab Jean Kuntzman, Grenoble, FranceTsinghua Univ, Beijing, Peoples R China
Wang, Yajun
Wang, Jiaping
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机构:Tsinghua Univ, Beijing, Peoples R China
Wang, Jiaping
Holzschuch, Nicolas
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机构:
INRIA Grenoble Rhone Alpes, Grenoble, France
CNRS, F-75700 Paris, France
Univ Grenoble, Lab Jean Kuntzman, Grenoble, FranceTsinghua Univ, Beijing, Peoples R China
Holzschuch, Nicolas
Subr, Kartic
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机构:
INRIA Grenoble Rhone Alpes, Grenoble, France
CNRS, F-75700 Paris, France
Univ Grenoble, Lab Jean Kuntzman, Grenoble, FranceTsinghua Univ, Beijing, Peoples R China
Subr, Kartic
Yong, Jun-Hai
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Tsinghua Univ, Beijing, Peoples R ChinaTsinghua Univ, Beijing, Peoples R China
Yong, Jun-Hai
Guo, Baining
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Tsinghua Univ, Beijing, Peoples R ChinaTsinghua Univ, Beijing, Peoples R China
机构:
Univ Calif Berkeley, Div Comp Sci, Dept EECS, Berkeley, CA 94720 USA
INRIA Rhone Alpes, F-38334 Saint Ismier, FranceUniv Calif Berkeley, Div Comp Sci, Dept EECS, Berkeley, CA 94720 USA
de Rousiers, Charles
Bousseau, Adrien
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INRIA Sophia Antipolis, FR-06902 Sophia Antipolis, FranceUniv Calif Berkeley, Div Comp Sci, Dept EECS, Berkeley, CA 94720 USA
Bousseau, Adrien
Subr, Kartic
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机构:
UCL, Dept Comp Sci, London WC1E 6BT, EnglandUniv Calif Berkeley, Div Comp Sci, Dept EECS, Berkeley, CA 94720 USA
Subr, Kartic
Holzschuch, Nicolas
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INRIA Rhone Alpes, F-38334 Saint Ismier, France
Lab Jean Kuntzmann, Grenoble, FranceUniv Calif Berkeley, Div Comp Sci, Dept EECS, Berkeley, CA 94720 USA
Holzschuch, Nicolas
Ramamoorthi, Ravi
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Univ Calif Berkeley, Div Comp Sci, Dept EECS, Berkeley, CA 94720 USAUniv Calif Berkeley, Div Comp Sci, Dept EECS, Berkeley, CA 94720 USA