Issued Patents All Time
Showing 25 most recent of 34 patents
| Patent # | Title | Co-Inventors | Date |
|---|---|---|---|
| 12374102 | Neural network control variates | Thomas Müller, Fabrice Rousselle, Alexander Keller | 2025-07-29 |
| 12169914 | Temporal techniques of denoising Monte Carlo renderings using neural networks | Thijs Vogels, Fabrice Rousselle, Brian McWilliams, Mark Meyer, Alex Harvill | 2024-12-17 |
| 11935179 | Fully-fused neural network execution | Thomas Müller, Nikolaus Binder, Fabrice Rousselle, Alexander Keller | 2024-03-19 |
| 11816404 | Neural network control variates | Thomas Müller, Fabrice Rousselle, Alexander Keller | 2023-11-14 |
| 11631210 | Fully-fused neural network execution | Thomas Müller, Nikolaus Binder, Fabrice Rousselle, Alexander Keller | 2023-04-18 |
| 11610360 | Real-time neural network radiance caching for path tracing | Thomas Müller, Fabrice Rousselle, Alexander Keller | 2023-03-21 |
| 11593988 | Fractional visibility estimation using particle density for light transport simulation | Eugene d″Eon, Jacopo Pantaleoni, Niko Markus Kettunen | 2023-02-28 |
| 11532073 | Temporal techniques of denoising Monte Carlo renderings using neural networks | Thijs Vogels, Fabrice Rousselle, Brian McWilliams, Mark Meyer, Alex Harvill | 2022-12-20 |
| 11037274 | Denoising Monte Carlo renderings using progressive neural networks | Thijs Vogels, Fabrice Rousselle, Brian McWilliams, Mark Meyer | 2021-06-15 |
| 10818080 | Piecewise-polynomial coupling layers for warp-predicting neural networks | Thomas Müller, Brian McWilliams, Fabrice Rousselle | 2020-10-27 |
| 10796414 | Kernel-predicting convolutional neural networks for denoising | Thijs Vogels, Fabrice Rousselle, Brian McWilliams | 2020-10-06 |
| 10789686 | Denoising Monte Carlo renderings using machine learning with importance sampling | Thijs Vogels, Fabrice Rousselle, Brian McWilliams, Mark Meyer | 2020-09-29 |
| 10706508 | Adaptive sampling in Monte Carlo renderings using error-predicting neural networks | Thijs Vogels, Fabrice Rousselle, Brian McWilliams, Mark Meyer, Alex Harvill | 2020-07-07 |
| 10699382 | Denoising Monte Carlo renderings using neural networks with asymmetric loss | Thijs Vogels, Fabrice Rousselle, Brian McWilliams, Mark Meyer, Alex Harvill | 2020-06-30 |
| 10672109 | Multi-scale architecture of denoising monte carlo renderings using neural networks | Thijs Vogels, Fabrice Rousselle, Brian McWilliams, Mark Meyer, Alex Harvill | 2020-06-02 |
| 10607319 | Denoising monte carlo renderings using progressive neural networks | Thijs Vogels, Fabrice Rousselle, Brian McWilliams, Mark Meyer | 2020-03-31 |
| 10586310 | Denoising Monte Carlo renderings using generative adversarial neural networks | Thijs Vogels, Fabrice Rousselle, Brian McWilliams, Mark Meyer | 2020-03-10 |
| 10580194 | Informed choices in primary sample space for light transport simulation | Wenzel Jakob, Wojciech Jarosz, Benedikt Bitterli | 2020-03-03 |
| 10572979 | Denoising Monte Carlo renderings using machine learning with importance sampling | Thijs Vogels, Fabrice Rousselle, Brian McWilliams, Mark Meyer | 2020-02-25 |
| 10565685 | Denoising binned-depth images | David M. Adler, Delio Aleardo Vicini, Brent Burley, Fabrice Rousselle | 2020-02-18 |
| 10475165 | Kernel-predicting convolutional neural networks for denoising | Thijs Vogels, Fabrice Rousselle, Brian McWilliams | 2019-11-12 |
| 10275934 | Augmented video rendering | Christopher Richard Schroers, Fabrice Rousselle, Matthias Fauconneau, Alexander Sorkine Hornung | 2019-04-30 |
| 10169910 | Efficient rendering of heterogeneous polydisperse granular media | Thomas Müller, Marios Papas, Wojciech Jarosz | 2019-01-01 |
| 10096088 | Robust regression method for image-space denoising | Benedikt Bitterli, Fabrice Rousselle | 2018-10-09 |
| 9916677 | Ray tracing across refractive boundaries | David Koerner, Wojciech Jarosz, Peter Kutz, Ralf Habel | 2018-03-13 |