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David Adler
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2020 – today
- 2024
- [c3]Yining Karl Li
, Charlotte Zhu
Cache Points for Production-Scale Occlusion-Aware Many-Lights Sampling and Volumetric Scattering. DigiPro 2024: 6
2010 – 2019
- 2019
- [j5]Delio Vicini
Denoising Deep Monte Carlo Renderings. Comput. Graph. Forum 38(1): 316-327 (2019) - [c2]Henrik Dahlberg, David Adler, Jeremy Newlin:
Machine-learning denoising in feature film production. SIGGRAPH Talks 2019: 21:1-21:2 - 2018
- [j4]Brent Burley, David Adler, Matt Jen-Yuan Chiang, Hank Driskill, Ralf Habel, Patrick Kelly, Peter Kutz, Yining Karl Li
The Design and Evolution of Disney's Hyperion Renderer. ACM Trans. Graph. 37(3): 33 (2018) - [j3]Thijs Vogels, Fabrice Rousselle
Denoising with kernel prediction and asymmetric loss functions. ACM Trans. Graph. 37(4): 124 (2018) - 2016
- [j2]Benedikt Bitterli, Fabrice Rousselle
Nonlinearly Weighted First-order Regression for Denoising Monte Carlo Renderings. Comput. Graph. Forum 35(4): 107-117 (2016) - 2015
- [j1]Henning Zimmer, Fabrice Rousselle
Path-space Motion Estimation and Decomposition for Robust Animation Filtering. Comput. Graph. Forum 34(4): 131-142 (2015)
1980 – 1989
- 1984
- [c1]Finley R. Shapiro, Stephen D. Senturia, David Adler:
The analysis of non-oscillating transients using the covariance method with many different orders. ICASSP 1984: 212-215
Coauthor Index
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