In an approach to calculating, filtering and presenting items, one or more computer processors identify a location of a user. The one or more computer processors determine one or more items that are relevant to the user. The one or more computer processors determine whether the user is within a threshold distance of the one or more items. The one or more computer processors calculate one or more weights for each of the one or more items. The one or more computer processors identify a device to present the one or more items. The one or more computer processors present the one or more weighted items based on the capabilities of the identified device.

An apparatus and method are described for a non-uniform rasterizer. For example, one embodiment of an apparatus comprises: a graphics processor to process graphics data and render images using the graphics data; and a non-uniform rasterizer within the graphics processor to determine different resolutions to be used for different regions of an image, the non-uniform rasterizer to receive a plurality of polygons to be rasterized and to responsively rasterize the polygons in accordance with the different resolutions.

A multi-terminal screen combination method, apparatus and device, and a computer storage medium. The method comprises the steps of: obtaining screen sizes of a reference terminal and a target terminal (S10); dividing, according to the screen dimensions, a picture to be displayed to generate display sub-pictures (S20); and displaying the display sub-picture corresponding to the reference terminal, and sending the other display sub-picture to the target terminal for display (S30). A function of combined display by means of a plurality of terminals is implemented.

3D data representing a three-dimensional structure is divided into a plurality of pieces and encoded, an obtained plurality of divided bitstreams is multiplexed, and one bitstream including a separator indicating a position of a joint between the divided bitstreams is generated. Furthermore, a separator indicating a position of a joint between divided bitstreams obtained by dividing 3D data representing a three-dimensional structure into a plurality of pieces and encoding the plurality of divided pieces of the 3D data, which is included in a bitstream obtained by multiplexing a plurality of the divided bitstreams, is analyzed, and the bitstream is divided into every divided bitstream on the basis of information included in the analyzed separator, and decoded. Applications of the technology include being implemented in, for example, an information processing apparatus, an image processing apparatus, electronic equipment, an information processing method, a program, or the like.

A system and method provides a video chat capability where the video portion of the chat is initially impaired, but gets progressively clearer, either as time elapses, or as the users speak or participate with relevant information.

An apparatus and method are described for a non-uniform rasterizer. For example, one embodiment of an apparatus comprises: a graphics processor to process graphics data and render images using the graphics data; and a non-uniform rasterizer within the graphics processor to determine different resolutions to be used for different regions of an image, the non-uniform rasterizer to receive a plurality of polygons to be rasterized and to responsively rasterize the polygons in accordance with the different resolutions.

3D data representing a three-dimensional structure is divided into a plurality of pieces and encoded, an obtained plurality of divided bitstreams is multiplexed, and one bitstream including a separator indicating a position of a joint between the divided bitstreams is generated. Furthermore, a separator indicating a position of a joint between divided bitstreams obtained by dividing 3D data representing a three-dimensional structure into a plurality of pieces and encoding the plurality of divided pieces of the 3D data, which is included in a bitstream obtained by multiplexing a plurality of the divided bitstreams, is analyzed, and the bitstream is divided into every divided bitstream on the basis of information included in the analyzed separator, and decoded. Applications of the technology include being implemented in, for example, an information processing apparatus, an image processing apparatus, electronic equipment, an information processing method, a program, or the like.

A digital asset management system is enhanced with an end-to-end deep zoom feature functionality that receives a user request to generate a deep zoom image of an asset, performs an image conversion if necessary, generates the deep zoom image and stores corresponding image folders and files in a transient storage separate from assets managed by the digital asset management system, and cleans up the deep zoom files after a pre-configured time period. The deep zoom image is rendered directly from the transient storage without having to involve the repository, which is separately managed by the digital asset management system. A new Web context is created and provided for viewing the deep zoom image within a browser-based user interface of the digital asset management system for a seamless user experience.

Neural network performance is improved in terms of training speed, memory footprint, and/or accuracy by learning a compressed neural graphics primitive representation. A neural graphics primitive is a mathematical function involving at least one neural network, used to represent a computer graphic, where the graphic can be an image, a 3D shape, a light field, a signed distance function, a radiance field, 2D video, volumetric video, etc. Instead of being input directly to a neural network, inputs are effectively mapped (encoded) into a higher dimensional space via a function. The input comprises coordinates used to identify a point within a d-dimensional space. The point is quantized and a set of vertex coordinates corresponding to the point are used to access an indexing codebook and a features codebook that store learned index offsets and learned feature vectors, respectively. The learned feature vectors are then provided as inputs to the neural network.

A system receives image data associated with an item, where the image data comprising a view of the item from two or more angles; determines physical attributes of the item; generates a base model of the item; samples the base model to generate one or more sampled models, each of the one or more sampled models comprising a subset of the geometric data, the subset of the geometric data determined based on one or more device characteristics of one or more user devices that interface with the system; receives device characteristics of a user device associated with a request from the user device for the item; selects, based on the received device characteristics, a sampled model of the item; and transmits a data object comprising the selected sampled model to the user device to cause the user device to generate a three-dimensional rendering of the item.