Abstract: The present application discloses an information processing method. The method includes: acquiring a resource package parameter determined by a sender client; invoking an interface with a second server, and acquiring a current conversion rate that is between the first-type resource and a second-type resource and is issued by the second server; calculating a quantity of second-type resources equal in value to the first quantity of first-type resources according to the conversion rate, and using the quantity as a second quantity; deducting the second quantity of second-type resources from a second-type resource account of the sender client, and generating at least one resource package, a sum of quantities corresponding to the at least one resource package being equal to the first quantity; and distributing the at least one resource package to at least one receiver client by using the link information.

Abstract: A communication method is provided for performance by a first network function entity. The communication method includes determining a service zone ID, transmitting information including the service zone ID to a second network function entity, where the service zone ID is used for the second network function entity to select a service producer instance from a service producer.

Abstract: A machine translation method includes: receiving to-be-processed information expressed in a source language; encoding the to-be-processed information, and generating an expression vector sequence of the to-be-processed information; and predicting feature information of a target foresight word at a first moment by using a prediction model. The feature information includes at least one of a part of speech or a word category of the target foresight word. The method also includes: determining a context vector corresponding to the first moment in the expression vector sequence according to the feature information of the target foresight word; and decoding the context vector by using a decoder, to obtain target content that corresponds to the context vector and expressed in a target language.

Abstract: This application relates to an interest recommendation method, a computer device, and a storage medium. The method includes: obtaining feature information of a target user; predicting interest similarities between the target user and a user group according to the feature information by using an interest similarity prediction model, the interest similarity prediction model being implemented according to an interest similarity between each pair of users in a sample set of historical records of users based on a hybrid tree-encoded linear model algorithm, the hybrid tree-encoded linear model algorithm being implemented based on a tree model and a linear model; determining, according to the interest similarities, recommended users in the user group having interests similar to those of the target user; and obtaining an interest list of the recommended users, and creating a recommendation list for the target user according to the interest list.

Abstract: An object detection training method can include receiving a training sample set in a current iteration of an object detection training process over an object detection neural network. The training sample set can include first samples of a first class and second samples of a second class. A first center loss value of each of the first and second samples can be determined. The first center loss value can be a distance between a feature vector of the respective sample and a center feature vector of the first or second class which the respective sample belongs to. A second center loss value of the training sample set can be determined according to the first center loss values of the first and second samples. A first target loss value of the current iteration can be determined according to the second center loss value of the training sample set.

Abstract: A collision data processing method includes: determining, based on a physical engine detecting that a first rigid body having a first physical attribute collides with a second rigid body having a second physical attribute, an initial cutting model from a first model corresponding to the first rigid body and a second model corresponding to the second rigid body based on the first physical attribute and the second physical attribute, capturing, by the physical engine, a collision point between the first rigid body and the second rigid body, and determining normal vector information corresponding to the collision point based on collision data, and determining a first cutting surface in the initial cutting model based on the collision point, the normal vector information, and model information of the initial cutting model, and cutting the initial cutting model based on the first cutting surface to obtain cutting data.

Abstract: An image gaze correction method, apparatus, electronic device, computer-readable storage medium, and computer program product. The image gaze correction method includes: acquiring a to-be-corrected eye image from a to-be-corrected image, generating, based on the to-be-corrected eye image, an eye motion flow field and an eye contour mask, the eye motion flow field being used for adjusting a pixel position in the to-be-corrected eye image, and the eye contour mask being used for indicating a probability that the pixel position in the to-be-corrected eye image belongs to an eye region, performing, based on the eye motion flow field and the eye contour mask, gaze correction processing on the to-be-corrected eye image to obtain a corrected eye image, and generating a gaze corrected image based on the corrected eye image.

Abstract: A detection method includes performing multiband filtering on a first area to obtain a plurality of band sub-images, the first area being an area in a first video frame, and performing multidirectional filtering on the plurality of band sub-images to obtain a plurality of direction sub-images. The method further includes acquiring a direction-band fused feature of the first area according to the plurality of direction sub-images, and inputting the direction-band fused feature into a detection model, and performing detection based on the direction-band fused feature using the detection model to detect whether the first area comprises an object.

Abstract: A service communication method, system, apparatus, electronic device, computer-readable storage medium, and computer program product; the method includes: receiving an authentication request sent by a service access process, performing synchronous verification processing on the service access process, and performing asynchronous verification processing on the service access process; determining service key information allocated for the service access process according to a synchronous verification processing result of the service access process, sending the service key information to the service access process to perform encrypted service communication with the service access process based on the service key information, and controlling a communication connection used for bearing the encrypted service communication with the service access process according to an asynchronous verification processing result of the service access process.

Abstract: Example embodiments provide a client live keeping method and apparatus, and a storage medium. The method includes: receiving, based on a client being switched to a background, a request including state information of a target state of the client at a current time and a target live keeping duration corresponding to the target state; transmitting the request to a terminal server; receiving, from the terminal server in response to the request, target information indicating live keeping information of the target state; and determining whether to perform live keeping on the target state based on the target information.

Abstract: A method for creating an interactive video is provided. In the method, an interactive video creation interface is displayed. The interactive video creation interface includes a video editing preview region and a component editing region. A first interactive clip is added to the video editing preview region. The first interactive clip includes a display scene. An information viewing component is added to a target position in the display scene of the first interactive clip based on selection of an information viewing option that is included in the component editing region. The information viewing component is configured to present information in the display scene when selected by a user of the interactive video. The interactive video is generated according to the information viewing component added to the first interactive clip.

Abstract: Prop control includes acquiring a trigger operation performed on a target shooting prop in an activated state in a virtual battlefield scene. The attack range of the target shooting prop may cover a partial area in the virtual battlefield scene. In response to the trigger operation, a target object targeted by the target shooting prop is determined. Using the target shooting prop, a plurality of continuous shooting actions are performed during a target time period on a target area in which the target object is located.

Abstract: A point cloud data encoding method is provided, which includes: acquiring initial point cloud data in a point cloud data processing environment; determining a space grid structure corresponding to the initial point cloud data; determining a filling order of different point cloud points in the initial point cloud data in the space grid structure; determining, based on the filling order of different point cloud points in the initial point cloud data in the space grid structure, residual information matched with the initial point cloud data; and encoding, according to the residual information, the initial point cloud data to obtain target point cloud data. A point cloud data decoding method, a point cloud data processing method, apparatuses, an electronic device, a computer program product, and a computer-readable storage medium are also provided.

Abstract: A method for delivering a virtual effect is provided. In the method, a target delivery point of the target virtual effect is determined based on a delivery point selection received from a user of a first virtual object. The target virtual effect is configured to change an attribute value of a second virtual object within an effect range of the target virtual effect. An actual delivery point of the target virtual effect is determined based on the target delivery point and one of a plurality of delivery precisions. The one of the plurality of delivery precisions is determined based on a delivery distance between the target delivery point and a position of the first virtual object. Delivery of the target virtual effect in a virtual environment is controlled based on the actual delivery point.

Abstract: This disclosure is directed to an image authenticity detection method and apparatus. The method includes: obtaining an image; removing low-frequency information from the image to obtain first image information of the image; denoising the first image information to obtain second image information; determining, based on a difference between the first image information and the second image information, a fixed pattern noise feature map corresponding to the image; analyzing distribution of fixed pattern noise in the fixed pattern noise feature map, the fixed pattern noise being inherent noise from a camera sensor and not interfered by image content; and detecting, based on the distribution, authenticity of the image to obtain an authenticity detection result of the image.

Abstract: A method and an apparatus for classifying an electroencephalogram signal, a device and a computer-readable storage medium. The method includes: obtaining an electroencephalogram signal; performing feature extraction on the electroencephalogram signal to obtain a signal feature corresponding to the electroencephalogram signal; obtaining a difference distribution ratio, the difference distribution ratio being used for representing impacts of difference distributions of different types on distributions of the signal feature and a source domain feature in a feature domain, the source domain feature being a feature corresponding to a source domain electroencephalogram signal; aligning the signal feature with the source domain feature according to the difference distribution ratio to obtain an aligned signal feature; and classifying the aligned signal feature to obtain a motor imagery type corresponding to the electroencephalogram signal.

Abstract: This application provides a method and apparatus for presenting an audiovisual work, a device, and a medium, and belongs to the field of artificial intelligence. The method includes: displaying a map control of the audiovisual work, the map control displaying a map associated with a plot of the audiovisual work; determining a marker point on the map in response to a location marking operation on the map; and presenting a plot clip in the audiovisual work that corresponds to the marker point.

Abstract: A cooperative vehicle-infrastructure processing method and apparatus, an electronic device, and a computer-readable storage medium are disclosed in embodiments of this application.

Abstract: An error model calibration method can analyze discrete distribution situations of a pseudo-range measurement error and a Doppler measurement error under different carrier-to-noise ratios and altitude helping to calibrate and improve the universality of error model calibration. Observation data is received and satellite data is acquired based on the observation data. A pseudo-range error array and a Doppler error array are calibrated based on the observation data, geometric parameters, and the satellite data. The pseudo range error array describes errors of two terminals under a carrier-to-noise ratio and altitude angle of a satellite. The Doppler error array describes a discrete distribution of the two terminals. The pseudo-range error models respectively corresponding to the at least two terminals are fit using the pseudo-range error array. The Doppler error models respectively corresponding to the at least two terminals are fit using the Doppler error array.

Abstract: An intelligent robot control method is provided for an intelligent robot. The method includes obtaining a first position at which the intelligent robot is currently located and a target position to be reached, and determining a movement path from the first position to the target position. The movement path has a particular roadblock. The method also includes transmitting a removal request when the intelligent robot moves from the first position to a second position, and a distance between the second position and a third position at which the particular roadblock is located and that is to be reached reaches a target distance. The removal request is used for requesting a removal instruction to be transmitted to the particular roadblock, and the removal instruction is used for, based on a roadblock type of the particular roadblock, instructing to remove the particular roadblock before the intelligent robot arrives.