Abstract: A method including receiving (S605) a request for a depth map, generating (S625) a hybrid depth map based on a device depth map (110) and downloaded depth information (105), and responding (S630) to the request for the depth map with the hybrid depth map (415). The device depth map (110) can be depth data captured on a user device (515) using sensors and/or software. The downloaded depth information (105) can be associated with depth data, map data, image data, and/or the like stored on a remote (to the user device) server (505).

Abstract: A method including receiving a prompt describing a desired characteristic of an image. The method further including generating, using a set of encoding models, a prompt encoding based on the prompt. The method further including generating, using a first transformer block of a diffusion transformer model, a first prompt embedding and a first image embedding based on the prompt encoding and a noise input. The method further including generating, using a second transformer block of the diffusion transformer model, a second image embedding based on the first image embedding and the first prompt embedding. The method further including generating the image based on the second image embedding.

Abstract: This specification describes systems and methods for refining point cloud data. Methods can include receiving point cloud data for a physical space, iteratively selecting points along an x, y, and z dimension, clustering the selected points into 2D histograms, determining a slope value for each 2D histogram, and removing, based on the slope value exceeding a predetermined value, points from the point cloud data. Methods can also include iteratively voxelizing each 2D histogram into predetermined mesh sizes, summating points in each voxelized 2D histogram, removing, based on determining the summation is below a predetermined sum value, points from the point cloud data, keeping, based on determining that a number of points in each voxelized 2D histogram exceeds a threshold value, a center point, selecting, for each histogram, a point, identifying, nearest neighbors in the point cloud data, removing the identified nearest neighbors from the data, and returning remaining points.

Abstract: A method of generating a user interface includes obtaining input data indicative of respective positions of a plurality of elements within an input plane and generating a model of a surface of a three-dimensional structure. The surface has circular symmetry and includes two curved polar caps and a curved equatorial belt, wherein a curvature of each of the polar caps is greater than a curvature of the equatorial belt. The method includes mapping the elements to respective positions on the model, and determining a position and orientation of a virtual camera, wherein the determined position of the virtual camera is exterior to the model. The method includes determining a field of view of the virtual camera containing a concave interior portion of the model, and rendering a projection of the model corresponding to the determined field of view and comprising elements mapped to positions on the concave interior portion.

Abstract: Various implementations disclosed herein include devices, systems, and methods that present a view of a device user's face portion, that would otherwise be blocked by an electronic device positioned in front of the face, on an outward-facing display of the user's device. The view of the user's face portion may be configured to enable observers to see the user's eyes and facial expressions as if they were seeing through a clear device at the user's actual eyes and facial expressions. Various techniques are used to provide views of the user's face that are realistic, that show the user's current facial appearance, and/or that present the face portion with 3D spatial accuracy, e.g., each eye appearing to be in its actual 3D position. Some implementations combine live data with previously-obtained data, e.g., combining live data with enrollment data.

Abstract: Methods, systems, and a computer program product are disclosed. The first method includes obtaining virtual session data in real time, identifying a positional utterance in the virtual session data, and generating a positional insight for the positional utterance. The first method also includes generating a best-practices recommendation based on the positional insight. The second method includes obtaining virtual session data, identifying positional utterances in the virtual session data, and generating positional insights for each of the positional utterances. The second method also includes selecting each of the positional insights having confidence scores above a threshold score and generating best-practices recommendations based on the selected positional insights.

Abstract: Systems and methods are provided for performing operations on an augmented reality (AR) device using an external screen streaming system. The system establishes, by one or more processors of an AR device, a communication with an external client device. The system causes overlay of, by the AR device, a first AR object on a real-world environment being viewed using the AR device. The system receives, by the AR device, a first image from the external client device. The system, in response to receiving the first image from the external client device, overlays the first image on the first AR object by the AR device.

Abstract: Apparatus and method for grouping rays based on quantized ray directions. For example, one embodiment of an apparatus comprises: An apparatus comprising: a ray generator to generate a plurality of rays; ray direction evaluation circuitry/logic to generate approximate ray direction data for each of the plurality of rays; ray sorting circuitry/logic to sort the rays into a plurality of ray queues based, at least in part, on the approximate ray direction data.

Abstract: One embodiment of the present invention sets forth a technique for generating actuation values based on a target shape such that the actuation values cause a simulator to output a simulated soft body that matches the target shape. The technique includes inputting a latent code that represents a target shape and a point on a geometric mesh into a first machine learning model. The technique further includes generating, via execution of the first machine learning model, one or more simulator control values that specify a deformation of the geometric mesh, where each of the simulator control values is based on the latent code and corresponds to the input point, and generating, via execution of the simulator, a simulated soft body based on the one or more simulator control values and the geometric mesh. The technique further includes causing the simulated soft body to be outputted to a computing device.

Abstract: In some implementations, a method includes obtaining a virtual object kit that includes a set of virtual object templates of a particular virtual object type. In some implementations, the virtual object kit includes a plurality of groups of components. In some implementations, each of the plurality of groups of components is associated with a particular portion of a virtual object. In some implementations, the method includes receiving a request to assemble a virtual object. In some implementations, the request includes a selection of components from at least some of the plurality of groups of components. In some implementations, the method includes synthesizing the virtual object in accordance with the request.

Abstract: The present specification describes examples of position-based switching of display devices. An example augmented reality (AR) device includes an AR display device to render display data. The example AR device also includes a wireless communication device to transmit and receive wireless signals. The example AR device further includes a processor to: 1) determine a position of the AR device relative to a computing device based on wireless signals communicated with the computing device; and 2) switch an activity state of the AR display device based on the determined position of the AR device relative to the computing device.

Abstract: Various implementations disclosed herein include devices, systems, and methods that generate a combined 3D representation of a user. For example, a process may include obtaining a first three-dimensional (3D) representation of a first portion of a user. The process may further include obtaining a sequence of frame-specific second 3D representations in a period of time, each of the frame-specific second 3D representations represent a second portion of the user. The process may further include generating a combined 3D representation of the user for the period of time by modifying the first 3D representation with a respective frame-specific second 3D representation.

Abstract: Images of an object may be captured via a camera at a mobile computing device at different viewpoints. The images may be used to identify components of the object and to identify damage estimates estimating damage to some or all of the components. Capture coverage levels corresponding with the components may be determined, and then recording guidance may be provided for capturing additional images to increase the capture coverage levels.

Abstract: A system comprises a processor and a memory having computer readable instructions stored thereon, which, when executed by the processor, cause the system to display an image of a surgical environment. The image includes an information icon corresponding to an instrument in the surgical environment. The instructions further cause the system to display an image of a body part of a user. The image of the body part is used to interact with the information icon. The instructions further cause the system to receive a gesture of the body part, via a gesture-based input device registering movement of the body part, to cause the image of the body part to interact with the information icon. The instructions further cause the system to display an information menu in the image of the surgical environment based on the interaction between the image of the body part and the information icon.

Abstract: Model data of a virtual model imitating an object model is generated based on photographed data obtained by photographing the object model including a joint structure. A given applied joint structure is applied to the virtual model. The virtual model based on the model data is disposed in a given virtual space. Virtual model management data including the model data and data of the applied joint structure is stored in a predetermined storage section or is externally output as data for causing a joint of the virtual model to function.

Abstract: Implementations relate to updating agricultural records that include inferences gathered by one or more sensors deployed at an agricultural location. The records are matched to mapping tiles of a mapping application and the mapping tile records are updated according to the updated data that was received. Implementations further include identifying parent tiles to each of the updated records, where a parent tile is an aggregation of multiple mapping tiles that can be utilized by a mapping application to render an interface that allows a user to view the data with varying degrees of granularity.

Abstract: Aspects of the present disclosure involve a system for presenting AR items. The system performs operations including: receiving an image that includes a depiction of a first real-world body part in a real-world environment; applying a machine learning technique to the image to generate a plurality of dense outputs each associated with a respective pixel of a plurality of pixels in the image; applying a first task-specific decoder to the plurality of dense outputs to identify a pixel corresponding to a center of the first real-world body part; applying a second task-specific decoder using the identified pixel to retrieve a 3D rotation, translation and scale of first real-world body part from the plurality of dense outputs; modifying an AR object based on the 3D rotation, translation, and scale of first real-world body part; and modifying the image to include a depiction of the modified AR object.

Abstract: The disclosure discloses an object comparison method and apparatus, relating to the technical field of computers. One specific implementation mode of the method comprises: acquiring, in response to a selection operation of at least two objects in an object list, corresponding object information according to identifiers of the at least two objects; performing, on the basis of each object information, three-dimensional model information rendering to obtain three-dimensional model information of each of the objects; and receiving image information of a real scenario to construct three-dimensional reconstruction information of the real scenario, and superimposing the three-dimensional model information of each of the objects onto the three-dimensional reconstruction information for display and comparison.

Abstract: A graphics processing hardware pipeline is arranged to perform an edge test or a depth calculation. Each hardware arrangement includes a microtile component hardware element, multiple pixel component hardware elements, one or more subsample component hardware elements and a final addition and comparison unit. The microtile component hardware element calculates a first output using a sum-of-products and coordinates of a microtile within a tile in the rendering space. Each pixel component hardware element calculates a different second output using the sum-of-products and coordinates for different pixels defined relative to an origin of the microtile. The subsample component hardware element calculates a third output using the sum-of-products and coordinates for a subsample position defined relative to an origin of a pixel.

Abstract: A system that includes a depth perception camera to estimate or otherwise measure the dimensions of a proposed carry-on item to determine whether the proposed carry-on item complies with limitations associated with a user. The system is configured to enable checking the proposed carry-on item and receiving payment for the checked item when the item exceeds the limitations associated with the user. Displayed to the user are dimension lines associated with the maximum dimensions of the limitations and/or the captured dimensions of the proposed carry-on item.