Monte Carlo rendering image denoising model, method and device based on generative adversarial network
US12223625B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Jun 5, 2020 |
| Grant date | Feb 11, 2025 |
| Priority date | — |
| Expiry date | Sep 20, 2041 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06T2207/20084
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
The present invention discloses a denoising model of Monte Carlo rendering based on a Generative Adversarial Network (GAN) and its construction method, including: constructing a training sample and constructing a Generative Adversarial Network (GAN), including Denoising Net and Critic Net, wherein Denoising Net is used to denoise the input noise rendering image and auxiliary features, and output the denoising rendering image, and Critic Net is used to classify the input denoising rendering image and the target rendering image corresponding to the noise rendering image, and output the classification result. The training samples are used to tune the network parameters of the Generative Adversarial Network (GAN). After the tuning is completed, the denoising network determined by the network parameters is used as the Monte Carlo rendering image denoising model. A denoising method and device for the Monte Carlo rendering image are also disclosed, which can realize the denoising of noisy Monte Carlo renderings.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.