When capturing and storing images, devices inevitably introduce noise. Reducing this noise
is a critical task called image denoising. Deep learning has become the de facto method for …

Ray tracing is an inherent part of photorealistic image synthesis algorithms. The problem of
ray tracing is to find the nearest intersection with a given ray and scene. Although this …

Sum-of-Squares Programming (SOSP) has recently been introduced to graphics as a unified
way to address a large set of difficult problems involving higher order primitives …

Image denoising based on deep learning has become a powerful tool to accelerate Monte
Carlo rendering. Deep learning techniques can produce smooth images using a low sample …

We present a novel technique for diffusing Monte Carlo sampling error as a blue noise in
screen space. We show that automatic diffusion of sampling error can be achieved by …

The need to evaluate integrals of high-dimensional signals arises in a number of
applications such as finance or machine learning. It is particularly crucial in global …

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 rendering is a computationally intensive task, but combined with recent deep-
learning based advances in image denoising it is possible to achieve high quality images in …

We contribute several practical extensions to the probe based irradiance-field-with-visibility
representation to improve image quality, constant and asymptotic performance, memory …

This article presents a solution to path tracing of massive scenes on multiple GPUs. Our
approach analyzes the memory access pattern of a path tracer and defines how the scene …