Abstract: A method and system for fingerprint positioning based on 5G multi-beam downlink signals, includes: extracting multi-beam SSB from 5G downlink signals, and obtaining multi-beam SSS signal and DM-RS signal from multi-beam SSB; calculating multi-beam reference signal received power RSRP based on multi-beam SSS signal and DM-RS signal; calculating the RSSI of 5G downlink synchronization channel based on multi-beam SSB autocorrelation, and calculating the multi-beam reference signal received quality RSRQ based on multi-beam RSRP and RSSI; stacking the multi-beam RSRP and RSRQ to form multi-beam fingerprint features; inputting multi-beam fingerprint characteristic into neural networks, and the neural networks output positioning results.

Abstract: The present invention discloses a method and system for multicarrier signal tracking based on deep learning and high precision positioning. Using the data characteristics of S-curve, and using S-curve which contains multipath signals as feature data for training deep learning networks under different signal-to-noise ratios. The delay regression results of receiving signal can be directly obtained by the S-curve of real-time receiving signal and the pre-trained network. The motivation of this method is to fully utilize the advantages of deep learning networks in accurately regressing complex problems with a large amount of data, fundamentally solving the impact of multipath signals on the delay estimation of the main path signal in traditional software defined receivers, extracting the corresponding relationship between the delay of main path and S-curve under the influence of different signal-to-noise ratios and different multipath signals.

Abstract: A method for training a three-dimensional face reconstruction model includes inputting an acquired sample face image into a three-dimensional face reconstruction model to obtain a coordinate transformation parameter and a face parameter of the sample face image; determining the three-dimensional stylized face image of the sample face image according to the face parameter of the sample face image and the acquired stylized face map of the sample face image; transforming the three-dimensional stylized face image of the sample face image into a camera coordinate system based on the coordinate transformation parameter, and rendering the transformed three-dimensional stylized face image to obtain a rendered map; and training the three-dimensional face reconstruction model according to the rendered map and the stylized face map of the sample face image.

Abstract: An image rendering method includes the steps below. A model of an environmental object is rendered to obtain an image of the environmental object in a target perspective. An image of a target object in the target perspective and a model of the target object are determined according to a neural radiance field of the target object. The image of the target object is fused and rendered into the image of the environmental object according to the model of the target object.

Abstract: The present disclosure discloses a method for processing a slider for a virtual character, an electronic device, and a storage medium, relating to a field of virtual reality, in particular to fields of artificial intelligence, Internet of Things, voice technology, cloud computing, etc. An implementation includes: acquiring a shape model associated with a target semantic tag; acquiring a skeleton and skinning information of a reference virtual character; fitting the shape model based on the skeleton and skinning information to obtain a skeleton linkage coefficient; and generating a slider associated with the target semantic tag based on the skeleton linkage coefficient, wherein the slider is used to drive the reference virtual character to obtain a target virtual character complying with a target semantic feature contained in the target semantic tag.

Abstract: A virtual image generation method and apparatus, an electronic device and a storage medium which relates to the field of artificial intelligence technologies such as augmented reality, computer vision and deep learning. A specific implementation scheme involves: acquiring base coefficients corresponding to key points of a target face based on a target face picture; generating a structure of a virtual image of the target face based on a mapping relationship of spatial alignment between a preset virtual model and a standard model, a base of the standard model and the base coefficients corresponding to the key points of the target face; and performing texture filling on the structure of the virtual image based on textures of the target face picture, to obtain the virtual image of the target face.

Abstract: The present disclosure belongs to technical field of indoor positioning, and discloses a method and system for wide-area acoustic indoor positioning based on RF enhancement, comprising: design of an acoustic signal, using Blackman window function to control the amplitude of acoustic signal entering and leaving channel; a mixed multiple access transmission of the acoustic signal, combining three multiple access schemes of time, space and frequency, assisting a small amount of BLE signals, and constructing a wide-area coverage capability of the acoustic positioning signal; acoustic measurement based on RF enhancement, including TOA estimation of an acoustic signal and area identification based on low-power Bluetooth RSS; robust fusion positioning of an inertial sensor and multi-source measurement, including pedestrian walking speed estimation, multi-source heterogeneous measurement, acoustic measurement compensation and correction, measurement quality evaluation and control.

Abstract: A preparation method of cemented carbide with FeCoCu medium-entropy alloy as binding phase is provided. The preparation method includes: 1) preparing FeCoCu precursor powders by solution combustion synthesis; 2) preparing FeCoCu medium-entropy alloy powders by mechanical alloying; 3) evenly mixing the FeCoCu medium-entropy alloy powders with ultra-fine WC powders and a binder to obtain mixed powders and pressing the mixed powders into a shaped green body; 4) preparing a WC-FeCoCu cemented carbide by microwave sintering after removing the binder from the shaped green body. The preparation method reduces sintering temperature and time and obtains a new-type cemented carbide with fine grains, high hardness and good toughness while reducing the cost.

Abstract: Embodiments of a method and apparatus for generating a virtual avatar, a device and a storage medium are provided. The method may include: determining a template coefficient of a target face in a to-be-processed image based on at least two real face feature templates; and determining a virtual avatar of the target face according to the template coefficient and at least two virtual face feature templates associated with the at least two real face feature templates.

Abstract: The present disclosure belongs to the technical field of acoustic positioning, and discloses an acoustic positioning system and method for a smartphone and a wearable device, and a terminal. A ranging signal is transmitted by virtue of a base station network, and specific space signals of which the frequencies are 12 kHz to 21 kHz are designed; the ranging signal is received and decoded by virtue of a user terminal, distances from base stations to the user terminal are estimated according to the first arrival signals, and the position of a user is estimated according to a plurality of distances measured on the position of the user. The present disclosure provides the acoustic positioning system (APS) for the smartphone and the wearable device, which is a technology for precise ranging based on acoustic waves.

Abstract: Embodiments of the present disclosure discloses a method and apparatus for rendering an image, an electronic device and a computer readable storage medium. An example implementation of the method includes: acquiring a real color parameter and a face skin color parameter in a real user image including a face image area, determining lighting parameter information based on the real color parameter and the face skin color parameter, acquiring a to-be-rendered image obtained based on the real user image, and generating a texture parameter based on the lighting parameter information, and using the texture parameter to perform lighting rendering on the to-be-rendered image to obtain a rendered image.

Abstract: A method and apparatus for generating a virtual character, an electronic device and a computer readable storage medium are provided. The method includes: performing mesh simplification on an initial model of a virtual character to obtain a mesh-simplified model; obtaining a first target model by performing white model mapping rendering on an area of each material type on the mesh-simplified model, and obtaining a second target model by performing hyper-realistic rendering on the area of each material type on the mesh-simplified model; and establishing a bidirectional mapping between the first target model and the second target model, and obtaining a target virtual character through iterative updating of the bidirectional mapping.

Abstract: A method of displaying an image, an electronic device, and a storage medium, which relate to an image processing field, in particular to fields of a three-dimensional display technology and a computer graphics technology, and are applied to augmented reality, virtual reality, mixed reality or other scenarios. The method includes: obtaining an adjusted parameter value in response to a triggering operation of an editing control for a parameter item to be adjusted; generating a three-dimensional avatar related to a target image, based on the adjusted parameter value, three-dimensional model data, and target image data of the target image; generating a preview image of the three-dimensional avatar according to the three-dimensional avatar; and displaying the three-dimensional avatar by using the adjusted parameter value, in response to a determination that a preview effect of the preview image meets an expected effect.

Abstract: The present disclosure provides a method for training an image editing model, a method for editing an image, apparatuses, a device, a storage medium and a computer program. An implementation plan is: acquiring a training sample set; and performing training steps as follows: selecting a description text sample and an image sample from the training sample set; determining a text direction vector based on the selected description text sample and a predetermined text template; inputting the text direction vector into a mapping network of the image editing model to obtain a bias vector; determining an image direction vector based on the selected image sample and the bias vector; calculating a loss value based on the text direction vector and the image direction vector; and determining, in response to the loss value meeting a threshold condition, that training of the image editing model is completed.

Abstract: An image processing method, an electronic device and a computer storage medium are provided, which relates to the fields of computer vision, augmented reality and artificial intelligence technologies. An implementation includes: acquiring a to-be-processed face image; reconstructing a face based on the to-be-processed face image to obtain a first blend coefficient vector based on a first blendshape base group; mapping the first blend coefficient vector to a second blendshape base group according to a pre-obtained coefficient mapping matrix between the first blendshape base group and the second blendshape base group to obtain a second blend coefficient vector based on the second blendshape base group; acquiring input face adjustment information, the face adjustment information including second blendshape base information; and obtaining a target face image based on the second blendshape base information and the second blend coefficient vector.

Abstract: The present disclosure provides a virtual image generation method and apparatus, an electronic device and a storage medium, and relates to the field of artificial intelligence technologies such as augmented reality, computer vision and deep learning. A specific implementation scheme involves: acquiring base coefficients corresponding to key points of a target face based on a target face picture; generating a structure of a virtual image of the target face based on a mapping relationship of spatial alignment between a preset virtual model and a standard model, a base of the standard model and the base coefficients corresponding to the key points of the target face; and performing texture filling on the structure of the virtual image based on textures of the target face picture, to obtain the virtual image of the target face.

Abstract: The present application discloses a method for operating a component, an electronic device, a storage medium and a program product, relating to the field of artificial intelligence technology, such as, the computer vision technology, the image processing technology and the augmented reality technology, the method includes: in response to a drawing operation on an operable component in a three-dimensional virtual space, displaying a drawn two-dimensional pattern on the operable component; in response to a model generating operation on the operable component, processing the two-dimensional pattern to generate a three-dimensional model; and displaying the three-dimensional model in the three-dimensional virtual space. In the solution provided by the present disclosure, an operable component which may be applied in a virtual space is provided, and a user may draw a pattern in the operable component, thus enabling a system to generate a three-dimensional model corresponding to the pattern.

Abstract: Provided are a method and an apparatus for determining a skeletal driving coefficient, an electronic device, and a readable storage medium, and relates to the field of image processing technologies, and in particular, to the field of artificial intelligence or augmented reality technologies. A method includes driving a deformation, based on an initial skeletal driving coefficient, on an initial skin-skeleton model to obtain a first skinned skeleton model; and in response to a difference between the first skinned skeleton model and a target skinned skeleton model does not meet a threshold, performing at least one deformation on the first skinned skeleton model until a second skinned skeleton model, the difference between which model and the target skinned skeleton model meets the condition on the difference, is obtained, and obtaining at least one target skeletal driving coefficient used for driving the at least one deformation.

Abstract: A face image processing method, an electronic device and a storage medium are provided, which relate to the technical fields of image processing, augmented reality, computer vision, deep learning and the like. The method includes: acquiring a three-dimensional face model of a to-be-processed face image, the three-dimensional face model comprising a plurality of grid nodes; determining a to-be-transformed area of the three-dimensional face model; acquiring a rigid transformation relationship between a standard three-dimensional face model and a standard stylized face model; and processing the to-be-transformed area based on the rigid transformation relationship, to obtain a stylized face model corresponding to the to-be-processed face image.

Abstract: The present disclosure discloses a method for generating a virtual image, an electronic device, and a storage medium, relating to a field of virtual reality, in particular to fields of artificial intelligence, Internet of Things, voice technology, cloud computing, etc. An implementation includes: acquiring a language description generated by a user for a target virtual character; extracting a respective semantic feature based on the language description; and generating the target virtual character based on the semantic feature.