Abstract: In one embodiment, a method includes a step of receiving a geometric representation of a virtual object and a texture atlas, the geometric representation comprising multiple geometric primitives defining a shape of the virtual object, the texture atlas comprises regions each of which is allocated to include shading information of a respective geometric primitive of the plurality of geometric primitives, and the shading information of the respective geometric primitive being scaled down to be smaller than the allocated region so as to create a buffer between the allocated region and adjacent regions of the plurality of regions on the texture atlas. The method further includes steps of identifying, based on a first viewpoint from which to view the virtual object, visible geometric primitives from the plurality of geometric primitives and rendering images of the visible geometric primitives using corresponding shading information included in the texture atlas.

Abstract: In one embodiment, a method includes the steps of receiving, from a client device, a first viewpoint from which to view a virtual object, the virtual object having a shape defined by multiple geometric primitives, identifying, relative to the first viewpoint, visible geometric primitives from multiple geometric primitives, allocating a region in a texture atlas for each of the visible geometric primitives, generating shading information for each of the visible geometric primitives, storing the shading information of each of the visible geometric primitives in a portion of the allocated region smaller than the allocated region to create a buffer around the portion of the allocated region where the shading information is stored, and sending, to the client device, the texture atlas and a list identifying the visible geometric primitives, the texture atlas being configured for rendering images of the visible geometric primitives from different viewpoints.

Abstract: A method includes the steps of receiving training data comprising images of an object and associated camera poses from which the images are captured, training, based on the training data, a machine-learning model to take as input a given viewpoint and synthesize an image of a virtual representation of the object viewed from the given viewpoint, generating, for each of predetermined viewpoints surrounding the virtual representation of the object, a view-dependent image of the object as viewed from that viewpoint using the trained machine-learning model, receiving, from a client device, a desired viewpoint from which to view the virtual representation of the object, selecting one or more of the predetermined viewpoints based on the desired viewpoint, and sending, to the client device, the view-dependent images associated with the selected one or more viewpoints for rendering an output image of the virtual representation of the object viewed from the desired viewpoint.

Abstract: In one embodiment, a method includes the steps of receiving, from a client device, a first viewpoint from which to view a virtual object, the virtual object having a shape defined by multiple geometric primitives, identifying, relative to the first viewpoint, visible geometric primitives from multiple geometric primitives, allocating a region in a texture atlas for each of the visible geometric primitives, generating shading information for each of the visible geometric primitives, storing the shading information of each of the visible geometric primitives in a portion of the allocated region smaller than the allocated region to create a buffer around the portion of the allocated region where the shading information is stored, and sending, to the client device, the texture atlas and a list identifying the visible geometric primitives, the texture atlas being configured for rendering images of the visible geometric primitives from different viewpoints.

Abstract: A method includes the steps of receiving training data comprising images of an object and associated camera poses from which the images are captured, training, based on the training data, a machine-learning model to take as input a given viewpoint and synthesize an image of a virtual representation of the object viewed from the given viewpoint, generating, for each of predetermined viewpoints surrounding the virtual representation of the object, a view-dependent image of the object as viewed from that viewpoint using the trained machine-learning model, receiving, from a client device, a desired viewpoint from which to view the virtual representation of the object, selecting one or more of the predetermined viewpoints based on the desired viewpoint, and sending, to the client device, the view-dependent images associated with the selected one or more viewpoints for rendering an output image of the virtual representation of the object viewed from the desired viewpoint.

Abstract: In one embodiment, a method includes the steps of generating, for a virtual object defined by a geometric representation, multiple viewpoints surrounding the virtual object, generating, for each of the multiple viewpoints, a simplified geometric representation of the virtual object based on the viewpoint, wherein the simplified geometric representation has a lower resolution than the geometric representation of the virtual object, receiving, from a client device, a desired viewpoint from which to view the virtual object, selecting one or more viewpoints from the multiple viewpoints based on the desired viewpoint, and sending, to the client device, rendering data including the simplified geometric representation and an associated view-dependent texture that are associated with each of the selected one or more viewpoints, the rendering data being configured for rendering an image of the virtual object from the desired viewpoint.

Abstract: A virtual reality or augmented reality experience of a scene may be decoded for playback for a viewer through a combination of CPU and GPU processing. A video stream may be retrieved from a data store. A first viewer position and/or orientation may be received from an input device, such as the sensor package on a head-mounted display (HMD). At a processor, the video stream may be partially decoded to generate a partially-decoded bitstream. At a graphics processor, the partially-decoded bitstream may be further decoded to generate viewpoint video of the scene from a first virtual viewpoint corresponding to the first viewer position and/or orientation. The viewpoint video may be displayed on a display device, such as screen of the HMD.

Abstract: A virtual reality or augmented reality experience of a scene may be decoded for playback for a viewer through a combination of CPU and GPU processing. A video stream may be retrieved from a data store. A first viewer position and/or orientation may be received from an input device, such as the sensor package on a head-mounted display (HMD). At a processor, the video stream may be partially decoded to generate a partially-decoded bitstream. At a graphics processor, the partially-decoded bitstream may be further decoded to generate viewpoint video of the scene from a first virtual viewpoint corresponding to the first viewer position and/or orientation. The viewpoint video may be displayed on a display device, such as screen of the HMD.