Enter inventor name

Average Co-Inventor Count = 4.7

ph-index = 5

Forward Citations = 64(Granted Patents)

Location History:

Zürich, CH (2017)
Zurich, CH (2018 - 2020)
Meilen, CH (2020 - 2023)

Company Filing History:

16 out of 2,771

Disney Enterprises, Inc.

Eth Zurich (eidgenoessische Technische Hochschule Zurich)

patents

4. 1 out of 1

Disnev Enterprises, Inc.

Eth Zurich (eidgenossische Technische Hochschule Zurich)

patents

where one patent can have more than one assignee

Years Active: 2017-2024

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18 patents (USPTO):Sort by Forward CitationsExplore Patents

1. 12169914 - Temporal techniques of denoising Monte Carlo renderings using neural networks (2024-12-17),

2. 11593988 - Fractional visibility estimation using particle density for light transport simulation (2023-02-28),

3. 11532073 - Temporal techniques of denoising Monte Carlo renderings using neural networks (2022-12-20),

4. 11037274 - Denoising Monte Carlo renderings using progressive neural networks (2021-06-15),

5. 10818080 - Piecewise-polynomial coupling layers for warp-predicting neural networks (2020-10-27),

6. 10789686 - Denoising Monte Carlo renderings using machine learning with importance sampling (2020-09-29),

7. 10706508 - Adaptive sampling in Monte Carlo renderings using error-predicting neural networks (2020-07-07),

8. 10699382 - Denoising Monte Carlo renderings using neural networks with asymmetric loss (2020-06-30),

9. 10672109 - Multi-scale architecture of denoising monte carlo renderings using neural networks (2020-06-02),

10. 10607319 - Denoising monte carlo renderings using progressive neural networks (2020-03-31),

11. 10586310 - Denoising Monte Carlo renderings using generative adversarial neural networks (2020-03-10),

12. 10572979 - Denoising Monte Carlo renderings using machine learning with importance sampling (2020-02-25),

13. 10565685 - Denoising binned-depth images (2020-02-18),

14. 10275934 - Augmented video rendering (2019-04-30),

15. 10169910 - Efficient rendering of heterogeneous polydisperse granular media (2019-01-01),

Title: Jan Novak: Innovator in Monte Carlo Rendering Techniques

Introduction

Jan Novak, a talented inventor based in Meilen, Switzerland, has made significant contributions to the field of computer graphics through his innovative techniques. With a remarkable portfolio of 18 patents, Jan has become a notable figure in the industry, particularly in the realm of denoising Monte Carlo renderings.

Latest Patents

Jan's latest patents showcase his cutting-edge work in enhancing visual rendering processes. One of his patents, titled "Temporal techniques of denoising Monte Carlo renderings using neural networks," introduces a modular architecture that efficiently denoises Monte Carlo renderings by utilizing neural networks. This innovative approach extracts and combines feature representations from neighboring frames, eliminating the need for recurrent connections, and incorporates multiscale architecture for customized denoising. His second patent, "Fractional visibility estimation using particle density for light transport simulation," dives into powerful methods for estimating transmittance through power-series expansion. This technique helps optimize the light transport simulation process by accurately evaluating the density function through a combination of samples.

Career Highlights

Throughout his career, Jan has been associated with prestigious companies such as Disney Enterprises, Inc. and Pixar. His work in these leading organizations has allowed him to hone his skills and drive innovation in the animation and visual effects industry.

Collaborations

Jan has collaborated with notable colleagues from the industry, including Brian McWilliams and Thijs Vogels. Their collective expertise has further advanced the research and development of novel techniques in computer graphics.

Conclusion

With a proven track record of pioneering patents and collaborations with industry giants, Jan Novak continues to shape the future of rendering technology. His dedication to innovation ensures that he remains a key player in the evolution of computer graphics.

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