Abstract: A data transmission method includes running a first application program on a first terminal, responding to an operation request for a document in the first application program to acquire a request object identifier and a document identifier of the document; acquiring a permission object group identifier of the document according to the document identifier, sending a permission authentication request for the request object identifier to the second application program, the permission authentication request being used to trigger the second application program to perform authentication processing on the request object identifier according to the permission object group identifier and return an authentication result, and outputting a response page of the operation request according to the authentication result returned from the second application program.

Abstract: In various examples, systems and methods are disclosed that relate to data augmentation for training/updating perception models in autonomous or semi-autonomous systems and applications. For example, a system may receive data associated with a set of frames that are captured using a plurality of cameras positioned in fixed relation relative to the machine; generate a panoramic view based at least on the set of frames; provide data associated with the panoramic view to a model to cause the model to generate a high dynamic range (HDR) panoramic view; determine lighting information associated with a light distribution map based at least on the HDR panoramic view; determine a virtual scene; and render an asset and a shadow on at least one of the frames, based at least on the virtual scene and the light distribution map, the shadow being a shadow corresponding to the asset.

Abstract: Approaches presented herein provide for the generation of visual content, including different types of content representations from different sources, rendered to include consistent scene illumination for the various representations. A first render pass can produce a first image including only proxies of implicit representations (e.g., NeRF objects) under scene illumination. A second render pass can produce a second image that includes a representation of the explicit scene objects, as well as the proxies of the implicit representations, under the scene illumination, which produces secondary lighting effects. The first and second images are compared to determine irradiance ratio data for the various pixel locations. A third render pass can produce a third image that includes the implicit representations, which can have relighting performed according to the irradiance ratio data to include the secondary lighting effects.

Abstract: An identification method of urban functional areas based on mixing degree of functions and integrated learning includes the following steps: 1) performing data acquisition and preprocessing; 2) constructing 10 indicator features of an urban functional area identification system; 3) structuring the indicator features: acquiring, by a spatial statistical tool, the 10 indicator features corresponding to each parcel; 4) constructing an independent variable dataset; 5) labeling response variables; 6) dividing a training dataset into a plurality of training subsets according to the mixing degree of functions; 7) training a Stacking-based integrated learning model; and 8) joining an attribute in one table to another table, so as to complete the identification of the urban functional areas on each parcel. The identification method divides the training dataset by grading the mixing degree of functions, and makes predictions based on the prediction dataset with corresponding mixing degree of functions.

Abstract: In various examples, information may be received for a 3D model, such as 3D geometry information, lighting information, and material information. A machine learning model may be trained to disentangle the 3D geometry information, the lighting information, and/or material information from input data to provide the information, which may be used to project geometry of the 3D model onto an image plane to generate a mapping between pixels and portions of the 3D model. Rasterization may then use the mapping to determine which pixels are covered and in what manner, by the geometry. The mapping may also be used to compute radiance for points corresponding to the one or more 3D models using light transport simulation. Disclosed approaches may be used in various applications, such as image editing, 3D model editing, synthetic data generation, and/or data set augmentation.

Abstract: Apparatuses, systems, and techniques are presented to generate digital content. In at least one embodiment, one or more neural networks are used to generate one or more textured three-dimensional meshes corresponding to one or more objects based, at least in part, one or more two-dimensional images of the one or more objects.

Abstract: In various examples, information may be received for a 3D model, such as 3D geometry information, lighting information, and material information. A machine learning model may be trained to disentangle the 3D geometry information, the lighting information, and/or material information from input data to provide the information, which may be used to project geometry of the 3D model onto an image plane to generate a mapping between pixels and portions of the 3D model. Rasterization may then use the mapping to determine which pixels are covered and in what manner, by the geometry. The mapping may also be used to compute radiance for points corresponding to the one or more 3D models using light transport simulation. Disclosed approaches may be used in various applications, such as image editing, 3D model editing, synthetic data generation, and/or data set augmentation.

Abstract: Systems and methods generate a hybrid lighting model for rendering objects within an image. The hybrid lighting model includes lighting effects attributed to a first source, such as the sun, and to a second source, such as spatially-varying effects of objects within the image. The hybrid lighting model may be generated for an input image and then one or more virtual objects may be rendered to appear as if part of the input image, where the hybrid lighting model is used to apply one or more lighting effects to the one or more virtual objects.

Abstract: An identification method of urban functional areas based on mixing degree of functions and integrated learning includes the following steps: 1) performing data acquisition and preprocessing; 2) constructing 10 indicator features of an urban functional area identification system; 3) structuring the indicator features: acquiring, by a spatial statistical tool, the 10 indicator features corresponding to each parcel; 4) constructing an independent variable dataset; 5) labeling response variables; 6) dividing a training dataset into a plurality of training subsets according to the mixing degree of functions; 7) training a Stacking-based integrated learning model; and 8) joining an attribute in one table to another table, so as to complete the identification of the urban functional areas on each parcel. The identification method divides the training dataset by grading the mixing degree of functions, and makes predictions based on the prediction dataset with corresponding mixing degree of functions.

Abstract: A data transmission method includes running a first application program on a first terminal, responding to an operation request for a document in the first application program to acquire a request object identifier and a document identifier of the document; acquiring a permission object group identifier of the document according to the document identifier, sending a permission authentication request for the request object identifier to the second application program, the permission authentication request being used to trigger the second application program to perform authentication processing on the request object identifier according to the permission object group identifier and return an authentication result, and outputting a response page of the operation request according to the authentication result returned from the second application program.

Abstract: In various examples, information may be received for a 3D model, such as 3D geometry information, lighting information, and material information. A machine learning model may be trained to disentangle the 3D geometry information, the lighting information, and/or material information from input data to provide the information, which may be used to project geometry of the 3D model onto an image plane to generate a mapping between pixels and portions of the 3D model. Rasterization may then use the mapping to determine which pixels are covered and in what manner, by the geometry. The mapping may also be used to compute radiance for points corresponding to the one or more 3D models using light transport simulation. Disclosed approaches may be used in various applications, such as image editing, 3D model editing, synthetic data generation, and/or data set augmentation.

Abstract: Certain example embodiments relate to a method for bonding slider row bars for a photolithography process. A holding device having a sticky surface is formed. A plurality of slider row bars is provided, with each having a first surface for forming an air bearing surface and a second surface opposite the first surface. The slider row bars are secured to the holding device with their first surfaces facing the sticky surface so that the first surfaces of the slider row bars are aligned each other. The slider row bars are bonded together by an encapsulating glue. A carrier is provided, and the carrier is bonded to the second surfaces of the slider row bars. The holding device is removed. The example embodiments also can be used to manufacture sliders.

Abstract: A method for bonding slider row bars for photolithography process, comprises steps of: (1) forming a holding device having a sticky surface; (2) providing a plurality of slider row bars each of which has a first surface for forming air bearing surface and a second surface opposite to the first surface, and securing the slider row bars on the holding device with their first surfaces facing to the sticky surface; (3) bonding the slider row bars together by an encapsulating glue; (4) providing a carrier and bonding the carrier to the second surfaces of the slider row bars; (5) removing the holding device. The invention also discloses a method for manufacturing sliders.

Abstract: A propulsion and stabilization system with a plurality of superconducting magnetic devices affixed to the dual-keels of a vehicle, where the superconducting magnetic devices produce a magnetic field when energized. The system also includes a plurality of figure-eight shaped null-flux coils affixed to opposing vertical sides of slots in a guideway. The figure-eight shaped null-flux coils are vertically oriented, laterally cross-connected in parallel, longitudinally connected in series, and continue the length of the vertical slots providing levitation and guidance force. An external power source energizes the figure-eight shaped null-flux coils to create a magnetic traveling wave that interacts with the magnetic field produced by the superconducting magnets to impart motion to the vehicle.