Monte Carlo (MC) integration is used ubiquitously in realistic image synthesis because of its
flexibility and generality. However, the integration has to balance estimator bias and …

Both the frame rate and the latency are crucial to the performance of realtime rendering
applications such as video games. Spatial supersampling methods, such as the Deep …

Participating media are frequent in real-world scenes, whether they contain milk, fruit juice,
oil, or muddy water in a river or the ocean. Incoming light interacts with these participating …

Various denoising methods have been proposed to clean up the noise in Monte Carlo (MC)
renderings, each having different advantages, disadvantages, and applicable scenarios. In …

Using a network trained by a large dataset is becoming popular for denoising Monte Carlo
rendering. Such a denoising approach based on supervised learning is currently considered …

Deep Combiner for Independent and Correlated Pixel Estimates Page 1 Deep Combiner for
Independent and Correlated Pixel Estimates JONGHEE BACK, Gwangju Institute of Science …

This article presents object-oriented neural light transfer (NeLT), a novel neural
representation of the dynamic light transportation between an object and the environment …

In this paper, we transfer machine learning techniques previously applied to denoising
surface-only Monte Carlo renderings to path-traced visualizations of medical volumetric …

Image-space denoising techniques have been widely employed in Monte Carlo rendering,
typically blending neighboring pixel estimates using a denoising kernel. It is widely …

Monte Carlo (MC) path tracing causes a lot of noise on the rendered image at a low samples
per pixel. Recently, with the help of inexpensive auxiliary buffers and the generative …