Abstract: An example electronic device may include a display module, a memory configured to store computer-executable instructions, and a processor configured to execute the instructions by accessing the memory. The processor may be configured to create a preliminary persona based on first information related to history of a target user, create a first persona from the preliminary persona based on second information related to a time and a space of the target user, apply the first persona to an avatar object in a virtual space and corresponding to the target user, and, when an occurrence of an event related to the target user is detected, create a second persona from the first persona based on the event occurrence and apply the second persona, instead of the first persona, to the avatar object.

Abstract: Devices, systems and processes for an integrated internal and external camera system that enhances the passenger experience in vehicles are described. One example method for enhancing a passenger experiences includes capturing a first set of images of an area around the vehicle using an external camera system, capturing a second set of images of one or more passengers inside the vehicle using an internal camera system, recognizing at least one gesture made by the one or more passengers based on the second set of images, identifying an object or a location external to the vehicle based on the first set of images and the at least one gesture, and displaying information related to the object or the location to the one or more passengers.

Abstract: An embodiment of the present disclosure provides a method for three-dimensional (3D) modeling. The method includes segmenting an image into a region of interest and a region of non-interest, and sending data associated with the region of interest to a server. The method further includes receiving a first 3D model corresponding to the region of interest from the server, the first 3D model being generated by a first neural network at the server; generating a second 3D model corresponding to the region of non-interest by a second neural network, the first neural network having more network parameters than the second neural network; and generating a 3D model corresponding to the image based on the first 3D model and the second 3D model. By using the method of an embodiment of the present disclosure, a processing speed of 3D modeling can be increased, and modeling quality and accuracy can be improved.

Abstract: Embodiments of the present disclosure provide an image processing method and apparatus, an electronic device, and a readable storage medium. The method includes: acquiring an image; detecting a target object in the image; performing, based on a posture of the target object, dancing effect rendering on the target object to generate an animation of the target object dancing; superimposing the animation on the image to obtain a dancing effect animation; and displaying the dancing effect animation. In the embodiment of the present disclosure, the object in the image can be rendered with a dancing effect to generate the animation of the object dancing.

Abstract: A method including receiving a three-dimensional scan of a coating that coats an object. The coating and the object, in combination, have a shape. The method also includes flattening the three-dimensional scan to generate flattened data. Flattening includes conforming scan data in the three-dimensional scan to zone data for zones of a layout. The zones represents sections of the shape cut along boundaries in the shape. Each of the zones represents a corresponding thickness of the coating in a corresponding section of the sections. The method also includes vectorizing the flattened data into a vector data structure. The method also includes generating a prediction whether one or more zones of the zones are out of an engineering tolerance for the coating. Generating the prediction is performed by a machine learning model that takes, as input, the vector data structure and produces, as output, the prediction.

Abstract: Methods, systems, and apparatus, including computer programs encoded on computer-storage media, for generating a placement of a camera. In some implementations, maintaining monitoring information of a property; generating a virtual model of a property; determining an initial placement location for a virtual camera in the virtual model; obtaining image data generated in the virtual model from the virtual camera placed at the initial placement location; analyzing the image data; determining, using the analysis of the image data, whether to identify an updated placement location; and providing the placement location for a physical camera at the property to a device using a result of the determination whether to identify the updated placement location.

Abstract: An artificial intelligence framework is described that incorporates a number of neural networks and a number of transformers for converting a two-dimensional image into three-dimensional semantic information. Neural networks convert one or more images into a set of image feature maps, depth information associated with the one or more images, and query proposals based on the depth information. A first transformer implements a cross-attention mechanism to process the set of image feature maps in accordance with the query proposals. The output of the first transformer is combined with a mask token to generate initial voxel features of the scene. A second transformer implements a self-attention mechanism to convert the initial voxel features into refined voxel features, which are up-sampled and processed by a lightweight neural network to generate the three-dimensional semantic information, which may be used by, e.g., an autonomous vehicle for various advanced driver assistance system (ADAS) functions.

Abstract: A display in a commercial passenger vehicle can an option to be locked or unlock to enhance security. An example system for securing an in-vehicle entertainment (IVE) display in a commercial passenger vehicle comprises a mobile device and a computer. The mobile device comprises a first processor configured to secure a display located in the commercial passenger vehicle, where the first processor is configured to: obtain a payload; generate a first digitally signed payload as a first output of a first mathematical computation performed on the payload with a secret key; and send a first message comprising the first digitally signed payload and a lock command to instruct the display to lock the display. The computer is communicably coupled with the display and comprises a second processor configured to send a first instruction to cause the display to lock in response to a reception of the lock command.

Abstract: Apparatuses, systems, and techniques to generate labels of objects depicted with in an image. In at least one embodiment, one or more object labels are generated in association with an image frame based, at least in part, on one or more prior frames and one or more subsequent frames.

Abstract: Various implementations disclosed herein include devices, systems, and methods that progressively capture data representing an actual appearance of a user for creating a 3D avatar of the user. Image sensors at a user's electronic device may capture images (or other sensor data) of different portions of a user's body over time. Images and other sensor data that is captured initially or at a given time may not represent all of the user's body. Thus, in some implementations, the progressively captured data provides representations of additional portions of the user's 3D avatar over time.

Abstract: Provided is an information processing apparatus including an information acquisition unit that acquires information regarding a length of a moving image template and information regarding a length of a material moving image to be fitted into the moving image template and a change processing unit that changes reproduction management information regarding the moving image template in order to adjust the length of the moving image template in accordance with the length of the material moving image.

Abstract: Some examples of the disclosure are directed to a virtual motion capture application configured to operate on a first electronic device. In some examples, the virtual motion capture application is configured to present, via the first electronic device, a user interface element containing an animation timeline and a virtual platter including a virtual object in a computer-generated environment. In some examples, the user interface element includes a plurality of options and tools for generating pose-centered motion for the virtual object in the computer-generated environment. In some examples, the virtual motion capture application is configured to exchange data corresponding to the virtual object with a content creation application running on a second electronic device. In some examples, the second electronic device may display a motion creation user interface associated with the content creation application while the first electronic device presents the computer-generated environment.

Abstract: The present disclosure discloses the use of machine learning to address the process of motion synthesis and generation of intermediate poses for virtual entities. A transformer-based model can be used to generate intermediate poses for an animation based on a set of key frames.

Abstract: Apparatuses, systems, and techniques to generate an image. In at least one embodiment, neural networks receive an inputted one or more images, generate feature and depth information, and a neural network uses said information to generate one or more images. In at least one embodiment, a processor comprises one or more circuits to use one or more first neural networks to generate one or more first images from a viewpoint outside of an object based, at least in part, on depth information generated using one or more second neural networks and feature information generated by one or more third neural networks. In at least one embodiment, Using a point cloud and a viewpoint as inputs, a third neural network generates an image of vehicle from said viewpoint while parking.

Abstract: Provided is an information processing apparatus capable of automatically executing processing according to a recognition result from a regression task. An acquirer acquires a first depth image that is a depth image of an area including a subject. Next, a pose estimator estimates coordinates of a plurality of feature points predetermined for the subject on the basis of the acquired first depth image. Then, a rendering unit generates a 3D CG model of the subject on the basis of the coordinates of the estimated feature points, and renders a second depth image obtained by imaging the generated 3D CG model with a virtual camera. Thereafter, a similarity calculator calculates similarity between the acquired first depth image and the rendered second depth image. Thereafter, the processing executor executes processing according to the calculated similarity.

Abstract: An optimization system reduces the data encoded within a point cloud for streaming and/or rendering of a lossy representation of the point cloud. The optimization system generates a first optimized splat for a first visual characteristic of the point cloud by replacing a first set of points having a first common value for the first visual characteristic with a first replacement primitive, and generates a second optimized splat for a second visual characteristic of the point cloud by replacing a second set of points having a second common value for the second visual characteristic with a second replacement primitive. The optimization system provides the first optimized splat and the second optimized splat instead of the original points of the point cloud in response to a request to access the point cloud.

Abstract: A streaming system and associated methods provide adaptive streaming of point cloud data for out-of-order presentation of important visual features before less important visual features. The adaptive streaming includes retrieving the points for a requested point cloud, differentiating different sets of points that represent different features in the point cloud, prioritizing each set of points based on a feature that is represented by that set of points, and streaming the different sets of points across a data network to a client device in an order that is determined from the prioritization. Moreover, the adaptive streaming may dynamically select a different subset of points from each set of points and different subset of point data to stream with each selected subset of points to visually convey important detail of each feature without all the corresponding points or data that make up that feature in the point cloud.

Abstract: Aspects of the disclosure relate to using machine learning models to automatically prioritize and orchestrate spatial data. A computing system may generate, based on inputting scene data and spatial positioning data into a machine learning model, a prioritized context that indicates physical objects that are significant within a physical environment. The scene data may comprise images of the physical environment and the spatial positioning data may comprise an indication of states of a user in the physical environment. Based on the prioritized context meeting user criteria, generate indications associated with the prioritized context. Based on the scene data, one or more spatial anchors at which to position the one or more indications of the prioritized context within a virtual environment based on the physical environment may be generated. The virtual environment comprising the indications of the prioritized context positioned at the one or more spatial anchors may be generated.

Abstract: The present disclosure relates to systems and methods for volume data rendering. The methods may include obtaining an initial image relating to volume data of a subject by performing a path tracing operation on the volume data, obtaining a total sampling operation count corresponding to the initial image, determining, based on the volume data, one or more reference parameters relating to the initial image, and generating, based on historical image data relating to the volume date of the subject, the initial image, the total sampling operation count, and the one or more reference parameters, a target image using an image processing model.

Abstract: A display program controls display of an activity in a virtual space, the activity being performed using a character operable by a user. The display program causes a computer to execute: displaying a first screen including the character and content, the content being based on details of the activity; and causing the display to transition to a second screen in response to an operation related to an action of the character, the second screen being different from the first screen and including a character corresponding to the character on the first screen, wherein the character on the first screen and the character on the second screen are different in at least one of form, state, and function, and for at least one of the character on the first screen and the character on the second screen, an animation imitating ears acts in response to an operation of the user.