Abstract:
A neural network-based rendering technique increases temporal stability and image fidelity of low sample count path tracing by optimizing a distribution of samples for rendering each image in a sequence. A sample predictor neural network learns spatio-temporal sampling strategies such as placing more samples in dis-occluded regions and tracking specular highlights. Temporal feedback enables a denoiser neural network to boost the effective input sample count and increases temporal stability. The initial uniform sampling step typically present in adaptive sampling algorithms is not needed. The sample predictor and denoiser operate at interactive rates to achieve significantly improved image quality and temporal stability compared with conventional adaptive sampling techniques.
Abstract:
A method, computer readable medium, and system are disclosed for redirecting a user's movement through a physical space while the user views a virtual environment. A temporary visual suppression event is detected when a user's eyes move relative to the user's head while viewing a virtual scene displayed on a display device, an orientation of the virtual scene relative to the user is modified to direct the user to physically move along a planned path through a virtual environment corresponding to the virtual scene, and the virtual scene is displayed on the display device according to the modified orientation.
Abstract:
A method, computer readable medium, and system are disclosed for computing a path for a user to move along within a physical space while viewing a virtual environment in a virtual reality system. A path for a user to physically move along through a virtual environment is determined based on waypoints and at least one characteristic of the physical environment within which the user is positioned, position data for the user is received indicating whether and how much a current path taken by the user has deviated from the path, and an updated path is computed through the virtual environment based on the waypoints and the at least one characteristic of the physical environment.
Abstract:
A method, computer readable medium, and system are disclosed for rendering shadows. A frustum projected from a grid cell corresponding to a light source in light-space is defined and a graphics primitive is determined to intersect the frustum. A light-space visibility buffer is accessed to obtain a set of pixel fragment footprints corresponding to the frustum and it is identified whether each pixel fragment footprint of the pixel fragment footprints is shadowed by the graphics primitive.
Abstract:
In computer graphics, texture refers to a type of surface, including the material characteristics, that can be applied to an object in an image. A texture may be defined using numerous parameters, such as color(s), roughness, glossiness, etc. In some implementations, a texture may be represented as an image that can be placed on a three-dimensional (3D) model of an object to give surface details to the 3D object. To reduce a size of textures (e.g. for storage and transmission), the present disclosure provides, in one embodiment, for compression of a texture set using a non-linear function and quantization. In another embodiment, the disclosure provides for compression of one or more textures using a non-linear function configured to compress textures with an arbitrary number of channels and/or an arbitrary ordering of channels.
Abstract:
A global illumination data structure (e.g., a data structure created to store global illumination information for geometry within a scene to be rendered) is computed for the scene. Additionally, reservoir-based spatiotemporal importance resampling (RESTIR) is used to perform illumination gathering, utilizing the global illumination data structure. The illumination gathering includes identifying light values for points within the scene, where one or more points are selected within the scene based on the light values in order to perform ray tracing during the rendering of the scene.
Abstract:
Motivated by the ability of humans to quickly and accurately detect visual artifacts in images, a neural network model is trained to identify and locate visual artifacts in a sequence of rendered images without comparing the sequence of rendered images against a ground truth reference. Examples of visual artifacts include aliasing, blurriness, mosaicking, and overexposure. The neural network model provides a useful fully-automated tool for evaluating the quality of images produced by rendering systems. The neural network model may be trained to evaluate the quality of images for video processing, encoding, and/or compression techniques. In an embodiment, the sequence includes at least four images corresponding to a video or animation.
Abstract:
A system, method, and computer program product are provided for performing object-space shading. A primitive defined by vertices in three-dimensional (3D) space that is specific to an object defined by at least the primitive is received and a shading sample rate is computed for the primitive based on a screen-space derivative of coordinates of a pixel fragment transformed into the 3D space. A shader program is executed by a processing pipeline to compute shaded attributes for the primitive according to the computed shading sample rate.
Abstract:
A system, method, and computer program product are provided for generating anti-aliased images. The method includes the steps of assigning one or more samples to a plurality of clusters, each cluster in the plurality of clusters corresponding to an aggregate stored in an aggregate geometry buffer, where each of the one or more samples is covered by a visible fragment and rasterizing three-dimensional geometry to generate material parameters for each sample of the one or more samples. For each cluster in the plurality of clusters, the material parameters for each sample assigned to the cluster are combined to produce the aggregate. The combined material parameters for each cluster are stored in an aggregate geometry buffer. An anti-aliased image may then be generated by shading the combined material parameters.
Abstract:
This application discloses techniques for generating and querying projective hash maps. More specifically, projective hash maps can be used for spatial hashing of data related to N-dimensional points. Each point is projected onto a projection surface to convert the three-dimensional (3D) coordinates for the point to two-dimensional (2D) coordinates associated with the projection surface. Hash values based on the 2D coordinates are then used as an index to store data in the projective hash map. Utilizing the 2D coordinates rather than the 3D coordinates allows for more efficient searches to be performed to locate points in the 3D space. In particular, projective hash maps can be utilized by graphics applications for generating images, and the improved efficiency can, for example, enable a game streaming application on a server to render images transmitted to a user device via a network at faster frame rates.