NVIDIA Corporation
Bayesian machine learning system for adaptive ray-tracing

Abstract:

Various techniques for adaptive rendering of images with noise reduction are described. More specifically, the present disclosure relates to approaches for rendering and denoising images--such as ray-traced images--in an iterative process that distributes computational efforts to pixels where denoised output is predicted with higher uncertainty. In some embodiments, an input image may be fed into a deep neural network (DNN) to jointly predict a denoised image and an uncertainty map. The uncertainty map may be used to create a distribution of additional samples (e.g., for one or more samples per pixel on average), and the additional samples may be used with the input image to adaptively render a higher quality image. This process may be repeated in a loop, until some criterion is satisfied, for example, when the denoised image converges to a designated quality, a time or sampling budget is satisfied, or otherwise.