Abstract: A data generation program includes instructions of: acquiring three-dimensional data representing a three-dimensional shape of a three-dimensional product; acquiring an arrangement condition for arranging a support member to the three-dimensional product; setting an extending direction, a width direction, and a height direction of the support member; adding a cutting margin of a particular thickness to a cutting surface of the three-dimensional product at one side in the height direction; setting the support member in accordance with the arrangement condition, one end of the support member in the extending direction being connected to the cutting margin added to the three-dimensional product; setting a beam, the beam being spaced from the three-dimensional product having the cutting margin in the extending direction, the beam extending in the width direction; generating three-dimensional modeling data for modeling a modeled object by using a three-dimensional modeling apparatus; and outputting the three-dimen

Abstract: A method for producing an image of a body tissue surface. The method includes transforming a source 3-D model of the body tissue surface into a flattened model comprising details of the body tissue surface represented visually on an unwrapped and flattened surface, wherein the flattened model represents transformed positions of the source 3-D model of the body tissue surface defined between a first edge and a second edge. The first edge is formed about a lumen defined by the body tissue surface, and the body tissue surface projects about the lumen to the second edge. The method further includes producing an image from the flattened model.

Abstract: A device receives an image including image data of a scale model of a vehicle, and processes the image data, with a model, to identify a make, a model, and a year represented by the scale model. The device determines augmented reality (AR) vehicle information based on the make, the model, and the year represented by the scale model of the vehicle, and provides the AR vehicle information to enable a user device to associate the AR vehicle information with the image of the scale model of the vehicle. The device receives an input associated with the AR vehicle information, and determines updated AR vehicle information based on the input associated with the AR vehicle information. The device provides the updated AR vehicle information to enable the user device to associate the updated augmented reality vehicle information with the image of the scale model of the vehicle.

Abstract: A system and method are disclosed to generate one or more mixed-reality visualizations and objects to facilitate efficient interaction with large volumes of data. Embodiments include a computer comprising a processor and memory and a mixed-reality display device comprising a display and one or more sensors. Embodiments generate a mixed-reality object comprising a first cuboid, the first cuboid comprising one or more adjustable display dimensions corresponding to one or more key process indicators (KPIs) and one or more cubelets divided along at least one of the one or more adjustable display dimensions. Embodiments display the mixed-reality object on the display, and adjust at least one of the one or more adjustable display dimensions in response to receiving a first input to the one or more sensors. In response to a second input, embodiments transform the one or more cubelets of the first cuboid.

Abstract: A method includes a computing device interpreting a request for a requesting entity to access a set of learning objects pertaining to a common topic represented in a virtual reality environment to produce a set of requested learning object identifiers. The method further includes determining whether a license smart contract for the set of learning objects associated with a non-fungible token of the object distributed ledger affirms access by the requesting entity to the set of learning objects. When access is affirmed, the method furth includes generating the virtual reality environment utilizing a group of object representations in accordance with interaction information for at least some of the object representations of the group of object representations. The method further includes outputting the virtual reality environment to the requesting entity for interactive consumption.

Abstract: An apparatus, computer readable storage medium and method of generating a diverse set of images from few-shot images, includes a parameter input receiving values for control parameters to control an extent to which each reference image impacts a newly generated image. The apparatus involves an image generation deep learning network for generating an image for each of the values for the control parameters. The deep learning network has an encoder, a transformer-based fusion block, and a decoder. The transformer-based fusion block includes a mapping network that computes meta-weights from features extracted from the reference images and the control parameters, and a cross-attention block to generate modulation weights based on the meta-weights. An output displays high-quality and diverse images generated based on the values for the control parameter.

Abstract: Systems and methods of generating a three-dimensional (3D) reconstruction of a scene or environment surrounding a user of a spatial computing system, such as a virtual reality, augmented reality or mixed reality system, using only multiview images comprising, and without the need for depth sensors or depth data from sensors. Features are extracted from a sequence of frames of RGB images and back-projected using known camera intrinsics and extrinsics into a 3D voxel volume wherein each pixel of the voxel volume is mapped to a ray in the voxel volume. The back-projected features are fused into the 3D voxel volume. The 3D voxel volume is passed through a 3D convolutional neural network to refine the and regress truncated signed distance function values at each voxel of the 3D voxel volume.

Abstract: Examples described herein provide a method that includes obtaining, by a processing device, three-dimensional (3D) voxel data. The method further includes performing, by the processing device, gray value thresholding based at least in part on the 3D voxel data and assigning a classification value to at least one voxel of the 3D voxel data. The method further includes defining, by the processing device, segments based on the classification value. The method further includes filtering, by the processing device, the segments based on the classification value. The method further includes evaluating, by the processing device, the segments to identify a surface voxel per segment. The method further includes determining, by the processing device, a position of a surface point within the surface voxel.

Abstract: In one example, a method includes causing presentation of a camera interface, the camera interface displaying a first image captured by a camera of a computing device of a first user of an interaction system, identifying a set of users of the interaction system that are associated with the first user, determining a subset of the set of users that have been active on the interaction system within a determinable time period, causing presentation, within the camera interface, of a graphical element for each user of the subset of users, each graphical element being user-selectable to invoke an augmentation mechanism, detecting user selection of a first graphical element associated with a second user of the subset, and causing presentation, within the camera interface and responsive to the detection of the user selection of the first graphical element, of an augmentation of the first image to generate augmented image.

Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for robot programming. One of the methods comprises generating an interactive user interface that includes an illustration of a first virtual robot, the first virtual robot having an initial pose that defines respective joint angles of one or more joints of the first virtual robot; receiving user input data specifying a target pose of the first virtual robot; and generating an animation of the first virtual robot transitioning between the initial pose and the target pose.

Abstract: Real-time monitoring of surroundings of a marine vessel. One or more observation sensor modules are configured and positioned to generate sensor data extending around the marine vessel. One or more data processors are configured to map and visualize the sensor data in relation to a virtual model of the marine vessel. A user interface is configured to display the virtual model together with the visualized sensor data from a user selectable point of view to a mariner of the marine vessel.

Abstract: Disclosed are systems and methods for voice-based control of augmented reality (AR) objects on a wearable device. The systems and methods perform operations comprising: instructing a display element of the AR wearable device to present a visual indicator representing a cursor; receiving voice input representing a first virtual object; determining a real-world position within a real-world environment being viewed through the AR wearable device based on a current position of the visual indicator; and instructing the display element of the AR wearable device to present the first virtual object within the real-world environment at the real-world position.

Abstract: The present disclosure relates to systems, non-transitory computer-readable media, and methods for generating and modifying digital animations based on user interactions with a unique user interface portraying a one-dimensional layer motion element and/or elements for generating and utilizing animation path for digital design objects and animation layers. The disclosed system can provide a dynamic one-dimensional layer motion element that adapts to a selected animation layer and portrays selectable animation frames from the animation layer. The disclosed systems can provide options for generating and modifying various frames of the digital animation based on user interactions with the one-dimensional layer motion element, an animation timeline, and/or a corresponding animation canvas.

Abstract: A computer-implemented method including: receiving visible-light images captured from viewpoints using visible-light camera(s); creating 3D model of real-world environment, wherein 3D model stores colour information pertaining to 3D points on surfaces of real objects (204); dividing 3D points into groups of 3D points, based on at least one of: whether surface normal of 3D points in group lie within predefined threshold angle from each other, differences in materials of real objects, differences in textures of surfaces of real objects; for group of 3D points, determining at least two of visible-light images in which group of 3D points is captured from different viewpoints, wherein said images are representative of different surface irradiances of group of 3D points; and storing, in 3D model, information indicative of different surface irradiances.

Abstract: An example method includes displaying, via a visualization device and overlaid on a portion of an anatomy of a patient viewable via the visualization device, a virtual model of the portion of the anatomy obtained from a virtual surgical plan for an orthopedic joint repair surgical procedure to attach a prosthetic to the anatomy; and displaying, via the visualization device and overlaid on the portion of the anatomy, a virtual guide that guides at least one of preparation of the anatomy for attachment of the prosthetic or attachment of the prosthetic to the anatomy.

Abstract: A GPU generates a plurality of images corresponding to a plurality of applications executed in parallel and stores the plurality of images in a frame buffer. A compression coder reads out the images stored in the frame buffer and codes the images. The compression coder reads out the plurality of images corresponding to the plurality of applications from the frame buffer at different timings for each application.

Abstract: The technology disclosed herein involves using a machine learning model (e.g., CNN) to expand lower dynamic-range image content (e.g., SDR images) into higher dynamic-range image content (e.g., HDR images). The machine learning model can take as input the lower dynamic-range image and can output multiple expansion maps that are used to make the expanded image appear more natural. The expansion maps may be used by image operators to smooth color banding and to dim overexposed regions or user interface elements in the expanded image. The expanded content (e.g., HDR image content) may then be provided to one or more devices for display or storage.

Abstract: Aspects of the present disclosure involve a system comprising a computer-readable storage medium storing a program and method for adding time-based captions to captured video. The program and method provide for displaying, by a messaging application, a preview user interface for previewing and editing captured video in order to generate a media content item, the preview user interface including an interface element which is selectable to switch to a captions user interface for adding a caption to the media content item; switching, in response to first user input selecting the interface element, to the captions user interface which is configured to receive user input for caption content and a duration to display the caption content; receiving, via the captions user interface, second user input for the caption content and the duration; and generating the media content item based on the caption content and the duration to display the caption content.

Abstract: Hairstyle transfer is challenging due to hair structure differences in the source and target hair. Latent Optimization of Hairstyles via Orthogonalization (LOHO) is an optimization-based approach using GAN inversion to infill missing hair structure details in latent space during hairstyle transfer. Hair is decomposed into three attributes: perceptual structure, appearance, and finer style, and includes tailored losses to model each of these attributes independently. Two-stage optimization and gradient orthogonalization enable disentangled latent space optimization of the three hair attributes. Using LOHO for latent space manipulation, users can synthesize novel photorealistic images by manipulating hair attributes either individually or jointly, transferring the desired attributes from reference hairstyles.

Abstract: Neural network systems and related machine learning methods for geological modeling are provided that employ an improved generative adversarial network including a generator neural network and a discriminator neural network. The generator neural network is trained to map a combination of a noise vector and a category code vector as input to a simulated image of geological facies. The discriminator neural network is trained to map at least one image of geological facies provided as input to corresponding probability that the at least one image of geological facies provided as input is a training image of geological facies or a simulated image of geological facies produced by the generator neural network.