Abstract: A processing device that causes a virtual-space image to be displayed on a display device mounted on a player's head is provided with a first display processor and a second display processor. The first display processor causes first external information input from outside to be displayed on a specified object included in the virtual-space image when the virtual-space image is being caused to be displayed by the HMD. The second display processor causes second external information that is second external information input from outside and includes a real-space image to be displayed along with the virtual-space image when the virtual-space image is caused to be displayed by the HMD. The virtual-space image is, for example, the virtual-space image of a game, and the real-space image is, for example, an image imaged by an imaging device installed in the surroundings of the player.

Abstract: A method for data processing and interactive information exchange with feature data extraction and bidirectional value evaluation for technology transfer is provided. During the process, a data processing instruction is formed after receiving a user operation instruction, and the corresponding data is obtained in accordance with the data processing instruction. Then, the corresponding data is processed to obtain specified data with feature data extraction; and the corresponding task for the specified data is being run to obtain a corresponding processing result, including a bidirectional value evaluation between the user and the processing result. A computer is also provided for use in connection with the method, where patent information is collected from the patent literature and subjected to processing, sorting, and analysis.

Abstract: The present disclosure relates to a method, device and product for managing a plurality of users of an application system. According to example implementations of the present disclosure, a method is provided for managing a plurality of users of an application system. In the method, a group of users matching a search keyword from a requester user are determined among the plurality of users, the search keyword comprising at least one part of an identifier of a desired user. A requester layer of the requester user is determined in a tree structure comprising hierarchical relations among the plurality of users. A group of layers of the group of users are determined in the tree structure, respectively. The group of users are sorted based on the requester layer and the group of layers. With example implementations of the present disclosure, a user which the requester user is looking for may be sorted at a top place so as to be selected by the requester user.

Abstract: In various examples, locations of directional landmarks, such as vertical landmarks, may be identified using 3D reconstruction. A set of observations of directional landmarks (e.g., images captured from a moving vehicle) may be reduced to 1D lookups by rectifying the observations to align directional landmarks along a particular direction of the observations. Object detection may be applied, and corresponding 1D lookups may be generated to represent the presence of a detected vertical landmark in an image.

Abstract: A super-resolution stereoscopic visualization processing system encompasses a base map database storing the 5 m-DEM base map, the 5 m-DEM mesh reading unit, a geographic-coordinates XYZ-point file, a plane-rectangular coordinate converter, a plane-rectangular XYZ-point file, a rasterization processor, a fine grid-cell memory, a smoothing processor, a smoothing image memory, a consideration-distance grid-number calculator, a red stereoscopic-visualization image generator, a red stereoscopic-visualization image memory, wherein a super-resolution red stereoscopic-visualization image of 5 m-DEM is obtained on a screen of a display.

Abstract: Provided is a method for generating a freehand sketch of a 3D model for machine learning, which is executed by one or more processors, in which a method for generating freehand sketch data for machine learning includes receiving a 3D model of a target object, and generating a plurality of different freehand sketch images for the target object based on the 3D model.

Abstract: A plugin can allow for tracking objects within a computer-aided design (“CAD”) application. In one example, the user can select an object or family of objects to track. The plugin can set a parameter of the tracker to match that of the selected object(s). The tracker can be joined to the selected object to form a new assembly, such as by embedding the tracker within the object. A user can define areas, such as rooms or floors, within the layout. The plugin can poll the trackers, which report which areas the corresponding object is within. The plugin can compile this information and display quantities of object types per area.

Abstract: Systems and techniques are described herein for modifying the scale and/or position of objects in images. For instance, a system can obtain a two-dimensional (2D) input image from a camera and a three-dimensional (3D) representation of the 2D input image. The system can further determine a first portion of the 3D representation of the 2D input image corresponding to a target object in the 2D input image. The system can adjust a pose of the first portion of the 3D representation of the 2D input image corresponding to the target object. The system can further generate a 2D output image having a modified version of the target object based on the adjusted pose of the first portion of the 3D representation of the 2D input image corresponding to the target object to be output on a display.

Abstract: A non-tokenized string is received. For example, a non-tokenized string could be a credit card number. The non-tokenized string is partitioned into a plurality of non-tokenized substrings. For example, if the credit card number is 16 digits long, it may be partitioned into substrings that are three, six, and seven digits in length. The non-tokenized substrings are used as an index into a plurality of lookup tables. As a result of the indexing, a plurality of tokenized substrings are retrieved. The plurality of tokenized substrings are combined into a tokenized string. The tokenized string is used as a token that represents the credit card number without disclosing the actual credit card number. The reverse of the above process can also occur.

Abstract: A system prioritizes the rendering and streaming of image data based on risk maps that predict change in a three-dimensional (“3D”) environment. The system receives primitives that are distributed across a 3D space to represent the 3D environment. The system generates a first image based on primitives that fall within a first view frustum, and generates a risk map with a risk value for each particular pixel of the first image. Each risk value quantifies a probability that a pixel of the first image associated with that risk value changes as a result of changing the first view frustum to a second view frustum. The system then performs an out-of-order rendering of primitives that fall within the second view frustum based on the risk value for each first image pixel that is replaced in a second image with a rendered primitive from the second view frustum.

Abstract: Provided are a computer program product, system, and method for determining user interactions with natural language processor (NLP) items in documents to determine priorities to present NLP items in documents to review. Information is received on user interactions with natural language processing (NLP) items in documents presented at least one computing device. Indication is made in a database of user interaction information on the user interactions with the NLP items indicated in the received transmitted information. The user interaction information in the database providing interaction information for NLP items in the selected document is used to determine an order of the NLP items in the selected document. Content of the NLP items in the selected document is transmitted to present to a reviewing user at a reviewing computing device in the determined order.

Abstract: Systems and methods to generate content styles for animation, and to adjust content styles by adjusting virtual style sliders for the content styles are disclosed. Exemplary implementations may: receive, from client computing platforms associated with users, style assignments for final compiled animation scenes; provide a style dial model with the style assignments and the corresponding final compiled animation scenes; train, from i) the style assignments, ii) the corresponding final compiled animation scenes, and iii) animation scene information that defines the final compiled animation scenes, the style dial model to determine individual style correlation values; receive user entry of levels of correlation to individual ones of multiple different content styles; input the animation scene and the levels of correlation to a model that outputs adjusted animation scene information that defines a styled compiled animation scene that has the selected levels of correlation to the individual content styles.

Abstract: Embodiments of the present invention provide systems, methods, and computer storage media for generating an animation of a talking head from an input audio signal of speech and a representation (such as a static image) of a head to animate. Generally, a neural network can learn to predict a set of 3D facial landmarks that can be used to drive the animation. In some embodiments, the neural network can learn to detect different speaking styles in the input speech and account for the different speaking styles when predicting the 3D facial landmarks. Generally, template 3D facial landmarks can be identified or extracted from the input image or other representation of the head, and the template 3D facial landmarks can be used with successive windows of audio from the input speech to predict 3D facial landmarks and generate a corresponding animation with plausible 3D effects.

Abstract: One embodiment provides techniques for automatically pre-labeling point cloud data with cuboid annotations. Point cloud data is processed using ML models to detect, associate, and localize objects therein, in order to generate cuboid tracks that each include a series of cuboid annotations associated with an object. An object detection model that detects objects and performs coarse localization is trained using a loss function that separately evaluates the distances between corners of predicted cuboids and corners of ground truth cuboids for position, size, and yaw. A refinement model that performs more accurate localization takes as input 2D projections of regions surrounding cuboid tracks predicted by the object detection model and the cuboid tracks, and outputs refined cuboid tracks. The refined cuboid tracks are filtered to a set of keyframes, with in-between frames being interpolated. The cuboid tracks can then be presented to a user for viewing and editing.

Abstract: A method for generating a dataset is provided. The method includes generating, within a simulated environment, a simulated image including one or more distortions, the simulated image includes a plurality of vehicles, generating vehicle image patches and ground truth from the simulated image, performing, using a style transfer module, a style-transfer operation on the vehicle image patches, combining the vehicle image patches, on which the style-transfer operation is performed, with a background image of a real-world location, and generating a dataset based on the ground truth and the combination of the vehicle image patches and the background image.

Abstract: Provided are a computer program product, system, and method for determining user interactions with natural language processor (NLP) items in documents to determine priorities to present NLP items in documents to review. Information is received on user interactions with natural language processing (NLP) items in documents presented at least one computing device. Indication is made in a database of user interaction information on the user interactions with the NLP items indicated in the received transmitted information. The user interaction information in the database providing interaction information for NLP items in the selected document is used to determine an order of the NLP items in the selected document. Content of the NLP items in the selected document is transmitted to present to a reviewing user at a reviewing computing device in the determined order.

Abstract: In an approach to creating and using a reinforcement learning model for personalizing a recommendation of a parking spot, one or more computer processors receive a first destination associated with the vehicle. One or more computer processors determine a parking spot availability in proximity to the destination. One or more computer processors determine a recommended parking spot location. One or more computer processors display the recommended parking spot location to the user. One or more computer processors determine a first parking spot selection. One or more computer processors receive a first satisfaction rating associated with the recommended parking spot location.

Abstract: A technique for performing ray tracing operations is provided. The technique includes initiating bounding volume hierarchy traversal for a ray against geometry represented by a bounding volume hierarchy; identifying multiple nodes of the bonding volume hierarchy for concurrent intersection tests; and performing operations for the concurrent intersection tests concurrently.

Abstract: Some implementations relate to methods, systems, and computer-readable media to generate text tags for games. In some implementations, a computer-implemented method to generate a 3D mesh for an object using a trained machine learning model includes providing a two-dimensional (2D) image of the object as input to the trained machine learning model, obtaining a template three-dimensional (3D) mesh, and generating, using the trained machine learning model and based on the 2D image and the template 3D mesh, a 3D mesh for the object, wherein the 3D mesh for the object is obtained by deforming the template 3D mesh and is usable to map a texture or to generate a 3D animation of the object.

Abstract: A computer-implemented method and system compresses CT reconstruction images and can include: receiving a volumetric density file including one or more voxels; replacing one or more voxel density values below an air density value with the air density value; replacing one or more voxel density values above a material density value with the material density value; determining one or more voxels of interest; replacing one or more non-interesting voxel density values below a material surface density with the air density value; replacing one or more non-interesting voxel density values above the material surface density with the material density value; quantizing all voxels to provide a reduced volume image; and compressing the reduced volume image to provide a compressed volume image.