Abstract: This application discloses an object control method and device, a storage medium and an electronic device. The method includes detecting a target angle generated in a process that a first target object performs an action combination during a game task, the action combination comprising performing a target action at least twice; triggering a state adjustment instruction in response to the target angle reaching a trigger threshold, the state adjustment instruction being used for instructing to adjust a movement state of the first target object; and adjusting, based on the state adjustment instruction, the movement state from a first state to a second state, a first time duration consumed by the first target object in the first state to complete the game task being longer than a second time duration consumed by the first target object in the second state to complete the game task.

Abstract: A data query method is provided. A data query request for a target data model is obtained. Based on the data query request and target metadata corresponding to the target data model, a target physical table corresponding to the data query request is determined from a plurality of physical tables corresponding to the target data model. The target metadata is determined based on the plurality of physical tables. The plurality of physical tables includes a basic table and a pre-aggregated table. The basic table is configured to record basic data of one granularity, and the pre-aggregated table is configured to record data of a plurality of granularities. Target query data corresponding to the data query request is obtained based on the data query request and the target physical table.

Abstract: This application provides a communication method performed at a control function entity. The method includes: receiving N first requests transmitted by N first network function (NF) entities, each of the first requests including a first valid time in which a first NF entity transmitting the first request provides a service; receiving a second request transmitted by a second NF entity, the second request being used for determining a third NF entity from the N first NF entities; and transmitting a first response to the second NF entity, the first response including a first valid time in which a third NF entity provides a service, such that the second NF entity performs service communication with the third NF entity within the first valid time in which the third NF entity provides the service, the third NF entity being included in the N first NF entities.

Abstract: The application provides a virtual video live streaming processing method and apparatus, an electronic device, and a computer-readable storage medium, and relates to the field of virtual video live streaming technologies. The virtual video live streaming processing method includes: obtaining text data and determining to-be-synthesized video data corresponding to the text data; synthesizing a live video stream in real time according to the to-be-synthesized video data and pushing the live video stream to a live streaming client; determining target video data from the to-be-synthesized video data that has not been synthesized into a live video stream in response to a live streaming interruption request during receiving a live streaming interruption request; and synthesizing an interruption transition video stream according to the target video data and pushing the interruption transition video stream to the live streaming client.

Abstract: A method for acquiring a texture of a three-dimensional (3D) model includes: acquiring at least two 3D networks generated by a target object based on a plurality of angles, the at least two 3D networks including a first correspondence between point cloud information and color information of the target object, and first camera poses of the target object; acquiring an offset between 3D points used for recording the same position of the target object in the at least two 3D networks according to the first camera poses respectively included in the at least two 3D networks; updating the first correspondence according to the offset, to acquire a second correspondence between the point cloud information and the color information of the target object; and acquiring a surface color texture of a 3D model of the target object according to the second correspondence.

Abstract: Embodiments of this application provide an image processing method and apparatus, an electronic device, and a storage medium. The method includes: acquiring a first sequence of images and motion vector data corresponding to each frame of image in the first sequence of images; generating, based on the motion vector data, the first sequence of images, and a slowdown multiple, an insertion image that correspondences to the slowdown multiple, a quantity of insertion images corresponding to the slowdown multiple; inserting the insertion image into a play sequence of the first sequence of images to obtain a second sequence of images; and playing the second sequence of images.

Abstract: A hand key-point recognition model training method is provided for a model training device. The method includes: converting a sample virtual image into an emulation image through a Cycle-GAN model, the sample virtual image being an image generated through three-dimensional modeling, and the sample virtual image including key-point coordinates corresponding to hand key-points, and the emulation image being used for emulating an image acquired in a real scenario; extracting a hand image in the emulation image; and training a hand key-point recognition model according to the hand image in the emulation image and the key-point coordinates, the hand key-point recognition model being used for outputting hand key-point coordinates of a hand in a real image according to the inputted real image.

Abstract: In an image optimization method, an image generation network, a to-be-optimized image, and a plurality of preset image features are obtained. A target feature is selected from the plurality of preset image features based on (i) the target feature and the to-be-optimized image and (ii) a preset similarity condition. The target feature and an initial offset parameter are input to the image generation network. The initial offset parameter is adjusted according to a difference between an output of the image generation network and the to-be-optimized image, to obtain a target offset parameter. The target feature and the target offset parameter are input to the image generation network, to generate an optimized image. Apparatus and non-transitory computer-readable storage medium counterpart embodiments are also contemplated.

Abstract: A processing method includes acquiring, by a first service node of a first blockchain, a cross-chain transfer request, the cross-chain transfer request including a virtual resource value, a first resource transfer-out address on the first blockchain, and a first resource transfer-in address on a second blockchain. The cross-chain transfer request is used by a second service node of the second blockchain to lock a first virtual resource of the virtual resource value in the second blockchain. The method further includes performing resource transfer-out processing on a second virtual resource associated with the virtual resource value in the first resource transfer-out address in response to a determination that the second service node locked the first virtual resource successfully. The method further includes transferring the first virtual resource to the first resource transfer-in address in the second blockchain in response to a determination that the second virtual resource was transferred out.

Abstract: Embodiments of this disclosure disclose a virtual item control method and apparatus, a terminal, and a non-transitory storage medium, and belong to the field of computer technologies. The method includes: displaying a plurality of item icons after a press operation on a throw button is detected; controlling, in response to the press operation moving to the target item icon and a duration reaches a target duration, a virtual object to hold a target virtual item corresponding to the target item icon; controlling, in response to a movement of the press operation, the virtual object to aim at a target position; and controlling, in response to a release of the press operation, the virtual object to throw the target virtual item to the target position.

Abstract: An image processing method including obtaining a fake template sample group comprising a first source image, a real labeled image, and a fake template image, inputting the fake template image into an identity swapping model to obtain a first identity swapping image of the fake template image, obtaining a fake labeled sample group comprising a second source image, a real template image, and a fake labeled image, the fake labeled image being based on identity swapping processing of the real template image, inputting the real template image into the identity swapping model to obtain a second identity swapping image of the real template image, and training the identity swapping model based on the fake template sample group, the first identity swapping image, the fake labeled sample group, and the second identity swapping image to generate a trained identity swapping model.

Abstract: An image processing method includes: determining a brightness value of an image; and enhancing a brightness of the image when the brightness value of the image is less than an image brightness threshold. Enhancing the brightness of the image includes: determining each pixel of the image as a target pixel; determining a brightness enhancement value of the target pixel based on the brightness value of the image, an initial brightness value of the target pixel, and initial brightness values of neighboring pixels of the target pixel; and using the brightness enhancement value as an enhanced brightness value of the target pixel.

Abstract: This disclosure relates to a role conversion method and apparatus. The method may include displaying a virtual environment. A first virtual object and a second virtual object are being displayed in the virtual environment. The method may further include obtaining a role conversion instruction for the first virtual object and converting the first virtual object to a target virtual object having a same role as the second virtual object in response to the role conversion instruction. The method may further include assigning a role attribute the same as that of the second virtual object to the target virtual object.

Abstract: An apparatus, method and storage medium for controlling a pathologic microscope are provided. The method includes obtaining a pathological digital image from an incident optical path of the pathologic microscope; performing artificial intelligence (AI) analysis on the pathological digital image to generate AI analysis information; and controlling an augmented reality (AR) projection component to project the AI analysis information on a microscopic field of the pathologic microscope on an outgoing optical path.

Abstract: Provided are an artifact removal method and apparatus based on machine learning (ML), and a method and apparatus for training an artifact removal model based on ML, in the field of artificial intelligence (AI). In the method, artifacts that may be generated in a process of compressing a video is preprocessed and removed by using an artifact removal model having a residual learning capability.

Abstract: A computer device obtains a to-be-segmented image that includes a plurality of extreme points corresponding to a target object in the to-be-segmented image. The device generates first image feature information according to the to-be-segmented image. The first image feature information includes N image matrices and a first heatmap that is generated according to the extreme points. The device obtains a first image segmentation region corresponding to the first image feature information using a first image segmentation model. The device also obtains a second heatmap according to an annotation point corresponding to the first image segmentation region and the first image segmentation region. The device obtains a second image segmentation region corresponding to the to-be-segmented image using a second image segmentation model. The device generates an image recognition result according to the second image segmentation region.

Abstract: A video content recognition method is performed by a computer device, the method including: obtaining an image feature corresponding to a video frame set extracted from a target video; dividing the image feature into a plurality of image sub-features according to a preset sequence, and each image sub-feature having a corresponding channel; choosing, from the image sub-features based on the preset sequence, a current image sub-feature; image sub-feature fusing the current image sub-feature and a convolution processing result of a previous image sub-feature into a fused image sub-feature, and performing convolution processing on the fused image sub-feature, to obtain a convolved image sub-feature corresponding to the current image sub-feature; splicing a plurality of convolved image sub-features corresponding to the plurality of channels of the convolved image sub-feature, to obtain a spliced image feature; and determining video content corresponding to the target video based on the spliced image feature.

Abstract: A method for controlling a virtual object to mark a virtual item is provided. The method includes: displaying a virtual environment picture, the virtual environment picture including the virtual object and the virtual item in a virtual environment; controlling the virtual object to move, in the virtual environment, into a proximity range of the virtual item; displaying a pick-up item list on the virtual environment picture, a field of the virtual item available for pick-up being displayed in the pick-up item list; and receiving a mark operation on the field of the virtual item, and marking the virtual item in the virtual environment according to the mark operation, the mark operation being an operation different from a pick-up operation.

Abstract: A method includes obtaining a first image to be rendered, obtaining a target mask image corresponding to the first image where a g component of the target mask image stores first light change data and a b component of the target mask image stores second light change data, the first light change data being change data of light on a left side of the first image used when the first image is rendered and the second light change data being change data of light on a right side of the first image used when the first image is rendered, and rendering the first image by using the target mask image to obtain a second image.

Abstract: A streaming method executed by a control device includes receiving a streaming media playback address of a cloud streaming service returned by a cloud device, and transmitting a media projection request corresponding to a local media file stored on the control device to a playback device. The method further includes transmitting a loading instruction indicating to start loading the virtual scene to the cloud device, generating initial file parameters corresponding to the local media file and replacing a file address of the local media file in the initial file parameters with the streaming media playback address to obtain modified file parameters. The method further includes returning the modified file parameters to the playback device, the modified file parameters providing the streaming media playback address instead of the initial file parameters corresponding to the local media file.