Nvidia Corporation

Alexey Panteleev

Yury Y Uralsky

Evgeny Makarov

Sergey Bolotov

Manuel Kraemer

Nuno Raposo Subtil

Mike Songy

Pawel Kozlowski

Henry Packard Moreton

Eric Brian Lum

Dmitry Duka

Cyril Crassin

Chris Wyman

Alexey Barkovoy

Tim Cheblokov

In examples, a filter used to denoise shadows for a pixel(s) may be adapted based at least on variance in temporally accumulated ray-traced samples. A range of filter values for a spatiotemporal filter may be defined based on the variance and used to exclude temporal ray-traced samples that are outside of the range. Data used to compute a first moment of a distribution used to compute variance may be used to compute a second moment of the distribution. For binary signals, such as visibility, the first moment (e.g., accumulated mean) may be equivalent to a second moment (e.g., the mean squared). In further respects, spatial filtering of a pixel(s) may be skipped based on comparing the mean of variance of the pixel(s) to one or more thresholds and based on the accumulated number of values for the pixel.

Spatiotemporal self-guided shadow denoising in ray-tracing applications

Systems and methods described relate to the generation of image content. In order to provide for smoothing between sequential images, but avoid introducing lag into lighting effects, light information can be compared for regions between consecutive rendered frames. Shading can be performed and the results compared for tiles of pixels to compute gradient values, such as by using a single light sample for each tile. A filtering pass can be performed with respect to these gradients, and this filtered, lower-resolution grid version can be upscaled into a full resolution, screen-sized image and the gradients transformed into confidence values. These confidence values can be used to determine an extent to which to keep lighting data from the previous frame with respect to the current frame. For example, less lighting information can be used from the prior frame for a given pixel location if the confidence for that location is lower.

Illumination resampling using temporal gradients in light transport simulation systems and applications

The disclosure provides a rendering system and a rendering method that split the pixels of a full frame into partial image fields and process those image fields individually in parallel. In one example, the rendering system includes: (1) an interface configured to receive a full frame, and (2) one or more processors, coupled to the interface, that split the full frame into a plurality of partial image fields, each of the partial image fields corresponding to different pixels of the full frame, process the partial image fields in parallel; and render the full frame using the processed partial image fields. The partial image fields are processed by ray tracing each of the partial image fields using a different type of ray in parallel.

Fine grained interleaved rendering applications in path tracing

Systems and methods of the present disclosure relate to fine grained interleaved rendering applications in path tracing for cloud computing environments. For example, a renderer and a rendering process may be employed for ray or path tracing and image-space filtering that interleaves the pixels of a frame into partial image fields and corresponding reduced-resolution images that are individually processed in parallel. Parallelization techniques described herein may allow for high quality rendered frames in less time, thereby reducing latency (or lag, in gaming applications) in high performance applications.

Fine grained interleaved rendering applications in path tracing for cloud computing environments

Devices, systems, and techniques to incorporate lighting effects into computer-generated graphics. In at least one embodiment, a graphical frame depicting a virtual scene comprising is rendered by generating a record indicative of one or more lights in the virtual scene, and using the record to render a pixel. A second record, indicative of other lights in the virtual scene, is selected to combine with the first record, based at least in part on similarity between surfaces associated with the respective records. The combined record is used to render a pixel in a second graphical frame.

Light-resampling with surface similarity test

Robust temporal gradients, representing differences in shading results, can be computed between current and previous frames in a temporal denoiser for ray-traced renderers. Backward projection can be used to locate matching surfaces, with the relevant parameters of those surfaces being carried forward and used for patching. Backward projection can be performed for each stratum in a current frame, a stratum representing a set of adjacent pixels. A pixel from each stratum is selected that has a matching surface in the previous frame, using motion vectors generated during the rendering process. A comparison of the depth of the normals, or the visibility buffer data, can be used to determine whether a given surface is the same in the current frame and the previous frame, and if so then parameters of the surface from the previous frame G-buffer is used to patch the G-buffer for the current frame.

Adaptive temporal image filtering for rendering realistic illumination

Apparatuses, systems, and techniques to render images. In at least one embodiment, at least one visibility parameter determined for a first image region is reused for a different second image region that neighbors the first image region (e.g., spatially and/or temporally).

Ray-traced light resampling using screen space visibility

Determining the occlusions or shadows for an area light within a scene is difficult, especially realistic shadowing in large and dynamic scenes. The disclosure provides an adaptive occlusion sampling process that uses voxel cone tracing to distribute the voxel tracing cones on the surface of area lights to obtain samples for shadowing in computer generated images or scenes. A method of adaptive occlusion sampling from a rectangular area light is disclosed that can be used to provide realistic shadowing in a computer generated scene. A process to compute a shadow of an area light within a scene is also disclosed herein that includes obtaining samples, employing voxel cone tracing, from a light surface of the area light based on sample points of a sampling grid created from sample patterns that are based on a determined number of cones.

Improving area light shadows in computer generated scenes

Area light shadows in computer generated scenes

The disclosure provides a renderer and a rendering process employing ray tracing and image-space filtering that interleaves the pixels of a frame into partial image fields and corresponding reduced-resolution images that are individually processed in parallel. In one example, the renderer includes: (1) an interface configured to receive scene information for rendering a full frame, and (2) a graphics processing system, coupled to the interface, configured to separate pixels of the full frame into different partial image fields that each include a unique set of interleaved pixels, render reduced-resolution images of the full frame by ray tracing the different partial image fields in parallel, independently apply image-space filtering to the reduced-resolution images in parallel, and merge the reduced-resolution images to provide a full rendered frame.

Approaches presented herein can reduce temporal lag that may be introduced in a generated image sequence that utilizes temporal accumulation for denoising in dynamic scenes. A fast historical frame can be generated along with a full historical frame generated for a denoising process, with the fast historical frame being accumulated using an exponential moving average with a significantly higher blend weight. This fast history frame can be used to determine a clamping window that can be used to clamp a corresponding full historical value before, or after, reprojection. The fast historical blend weight can be adjusted to control the amount of noise versus temporal lag in an image sequence. In some embodiments, differences between fast and full historical values can also be used to determine an amount of spatial filtering to be applied.

Growing community of inventors

Los Gatos, CA, United States of America

Alexey Panteleev