Abstract: Disclosed is a method for training an expression transfer model performed by a computer device, the method including: obtaining a source domain facial image of a first object, a target domain facial image of a second object and a facial feature image associated with the target domain facial image; applying the facial feature image and the source domain facial image to an expression transfer model to obtain a synthesized facial image of the first object; applying the synthesized facial image and the target domain facial image to a discriminative network model obtain two discrimination results; applying the synthesized facial image and the target domain facial image to an image classification model to obtain a category feature vector for identifying a difference between the synthesized facial image and the target domain facial image; and updating the expression transfer model according to the category feature vector and the discrimination results.

Abstract: The present application provides an image detection method performed by a server. The method includes: intercepting a first image and a second image at a preset time interval from a video stream; performing pixel matching on the first image and the second image to obtain a value of total matching pixels between the first image and the second image; performing picture content detection on the second image in response to determining that the value of total matching pixels between the first image and the second image satisfies a preset matching condition based on the value of total matching pixels; and determining that the video stream is abnormal in response to determining that no picture content is in the second image by the picture content detection. In this way, an image recognition manner can be used to perform detection on image pictures of the video stream at the preset time interval.

Abstract: A method, computer program, and computer system is provided for compressing a neural network model. A multi-dimensional tensor corresponding to a set of weight coefficients associated with a neural network is reshaped. A subset of weight coefficients is identified from among the set of weight coefficients. A model of the neural network is compressed based on the identified subset of weight coefficients.

Abstract: An inter prediction method includes: determining, when a current prediction mode of a current prediction block is a preset prediction mode, a historical prediction mode corresponding to the current prediction block; acquiring adjacent block information about an adjacent block of the current prediction block, prediction sub-block information about a prediction sub-block, and a historical optimal reference frame type of the current prediction block in the historical prediction mode; generating a reference frame mask based on the historical optimal reference frame type, the adjacent block information, the prediction sub-block information, and a frame type corresponding to the current prediction block; and determining a reference frame of the preset prediction mode using the reference frame mask, and performing inter prediction on the current prediction block using the reference frame to obtain a prediction value corresponding to the current prediction block.

Abstract: This application discloses a block chain-based data processing method performed by a computer device, including: acquiring a pending transaction including a pending execution order identifier; adding, when determining that the pending transaction is in the prepared state, the pending transaction and the pending execution order identifier to the pending account ready queue to obtain a transitional account ready queue; using an execution order identifier that forms a continuous sequence of order identifiers with the pending execution order identifier as an upgraded execution order identifier in the pending account waiting queue, and adding the upgraded execution order identifier and a waiting transaction corresponding to the upgraded execution order identifier to the transitional account ready queue in sequence to obtain an upgraded account ready queue; and adding the pending transaction and the waiting transaction corresponding to the upgraded execution order identifier in the upgraded account ready queue to a

Abstract: Disclosed are an image processing method and apparatus, a computer device and a storage medium, which relate to the field of artificial Intelligence. The method includes receiving an original image; performing image photographing defect detection and color deviation detection on the original image, the image photographing defect detection determining whether there exists a photographing defect that is irreparable through image processing, the color deviation detection determining whether there exists color cast in the original image; performing color correction on the original image if the original image passes the image photographing defect detection and does not pass the color deviation detection; and generating a target image based on the color-corrected original image.

Abstract: A deep learning-based video editing method can allow for automated editing of a video, reducing or eliminating user input, saving time and labor investments, and thereby improving video editing efficiency. Attribute recognition is performed on an object in a target video using a deep learning model. A target object is selected that satisfies an editing requirement of the target video. A plurality of groups of pictures associated with the target object from the target video are obtained using editing. An edited video corresponding to the target video is generated using the plurality of groups of pictures.

Abstract: This application provides a method for controlling vehicles to drive as a platoon performed by an electronic device. The method includes: transmitting, from a leading vehicle, a first platoon disbanding message to a target non-tail following vehicle and a second platoon disbanding message to the other remaining following vehicles, the second message including a temporary disbanding instruction for instructing to temporarily disband the current vehicle platoon, so that the target non-tail following vehicle adjusts a status thereof to a free status and drives away from the current vehicle platoon; transmitting, from the leading vehicle, a re-team up invitation message to each of the remaining following vehicles according to the second platoon disbanding message; receiving, at a leading vehicle, a re-team up confirmation message; and reorganizing each of the remaining following vehicles according to the re-team up confirmation message to form a new vehicle platoon.

Abstract: A data transmission method and apparatus, a terminal, a storage medium, and a system. The data transmission method includes: obtaining audio data and transmission status information, determining a compression factor and a redundancy factor based on the transmission status information, performing time domain data compression processing on the audio data according to the compression factor to obtain compressed data, performing channel coding on the compressed data according to the redundancy factor to obtain a data transmission packet, and transmitting the data transmission packet.

Abstract: Neural image compression using substitutional quality factor learning in a latent space, including receiving a compressed bitstream and a target quality factor indicating a target compression quality, calculating a decoded latent representation of the compressed bitstream, and calculating a reconstructed image based on the decoded latent representation of the compressed bitstream and the target quality factor, computing a shared feature based on a network forward computation using shared decoding parameters (SDP) of one or more layers of a convolutional neural network, computing estimated adaptive decoding parameters (ADP) for the one or more layers of the convolutional neural network based on the shared feature, the adaptive decoding parameters, and the target quality factor, and computing an output tensor based on the estimated ADP in the one or more layers of the convolutional neural network and the shared feature.

Abstract: Embodiments of this application disclose a virtual scene display method performed by a computer device, which relate to the field of virtual scene technologies. The method includes: generating a virtual scene interface, the virtual scene interface including a scene image of a virtual scene captured by a virtual camera; displaying, in the virtual scene interface, a first scene image of one or more virtual objects in the virtual scene captured by the virtual camera using a first representation, the first representation being one of a 2D representation and a 3D representation; and in response to receiving a zoom operation on the virtual scene, displaying, in the virtual scene interface, a second scene image of the one or more virtual objects in the virtual scene captured by the virtual camera using a second representation, the second representation being the other one of the 2D representation and the 3D representation.

Abstract: Aspects of the disclosure provide methods, apparatuses, and non-transitory computer-readable storage mediums for receiving media data. One apparatus includes processing circuitry that receives a timed metadata track of a plurality of segments including a plurality of metadata samples. A duration of each of the plurality of segments is equal to a duration of a metadata sample included in the respective segment. A correct timing of each of the plurality of metadata samples is maintained during fragmentation and defragmentation processes that are performed on the timed metadata track. The processing circuitry determines a presentation time of one of the plurality of metadata samples. The processing circuitry processes event information included in one or more event message boxes included in the one of the plurality of metadata samples based on the presentation time of the one of the plurality of metadata samples.

Abstract: A data transmission method includes: receiving access stratum context information transmitted by an AMF; detecting, in response to identifying that a data packet transmitted by a UPF through the GTP-U tunnel belongs to sub-data packets obtained by splitting the advanced interactive data packet, whether there is a sub-data packet that fails to transmit in the sub-data packets obtained by splitting the advanced interactive data packet during transmitting the sub-data packets to a user equipment on the basis of the DRB; and stopping transmitting the remaining sub-data packets obtained by splitting a specified type of advanced interactive data packet to the user equipment in response to detecting that there is a sub-data packet that fails to transmit in the sub-data packets obtained by splitting the specified type of advanced interactive data packet.

Abstract: A method of video decoding includes reconstructing a coded picture including at least a first sample. The coded picture is associated with a Supplemental Enhancement Information (SEI) message for a film grain synthesis process to be applied to the reconstructed picture. The SEI message for the film grain synthesis process includes a syntax element indicating that alpha channel information is used in the film grain synthesis process. The method of video decoding includes applying the film grain synthesis process to the first sample based at least on the alpha channel information.

Abstract: A method of processing a video bitstream includes receiving the video bitstream comprising (i) one of a picture and a video and (ii) a supplemental enhancement information (SEI) message associated with the one of the picture and the video. The SEI message includes text data purposed for use with a generative artificial intelligence (AI) process. The method of processing the video bitstream includes extracting the text data from the SEI message. The SEI message does not indicate whether the one of the picture and the video has been modified by another generative AI process.

Abstract: A method is provided for adjusting a perceived map location of a first player in a video game. The method includes determining whether the perceived map location of a virtual game asset of a first player of the game starting from a first location on a map of a virtual environment is to be displayed as starting from a second location on the map, the first location is symmetrical from the second location about a reference point on the map. The method includes, based on a determination that the perceived map location is to be displayed as starting from the second location, adjusting a location of the virtual game asset on the map to an adjusted location for display on a device displayed map according to the second location. The method further includes displaying the virtual game asset of the first player at the adjusted location on the device displayed map.

Abstract: A virtual object animation generation method and apparatus including obtaining a to-be-processed video, determining initial 3D pose information, two-dimensional (2D) pose information, and foot ground contact information of a target object in the to-be-processed video, determining pose change information between two adjacent video frames in the to-be-processed video based on the initial 3D pose information of the target object, determining to-be-corrected pose information of the target object based on the initial 3D pose information of the target object and the pose change information, performing correction processing on the to-be-corrected pose information of the target object based on the 2D pose information and the foot ground contact information of the target object, to obtain corrected pose information of the target object, and retargeting the corrected pose information to a virtual object by means of motion retargeting, to generate a virtual object animation video corresponding to the to-be-processed vid

Abstract: A method is provided, in which infrastructure configuration parameters received from a configuration management database are converted into an infrastructure-as-code configuration language file. Infrastructure configuration modifications are applied to the infrastructure-as-code configuration language file. The modified infrastructure-as-code configuration language file is forwarded to an infrastructure-as-a-service provider. Provisional infrastructure-as-code parameters output by the infrastructure-as-a-service provider in response to the modified infrastructure-as-code configuration language file are converted to updated infrastructure configuration parameters. The updated infrastructure configuration parameters are transmitted for storage in the configuration management database.

Abstract: An image quality detection method includes, obtaining an input image; recognizing a target element in an input image, and obtaining a target element region of the input image in which the target element is located; extracting a current region feature corresponding to the target element region; obtaining category features corresponding to preset image quality categories; comparing the current region feature with the category features, to obtain matching degrees between the current region feature and the category features, and determining a target category feature corresponding to the current region feature from the category features based on the matching degrees; and determining a target region quality category of the target element region based on a target preset image quality category corresponding to the target category feature, and outputting a predicted image quality category of the input image based on the target region quality category.

Abstract: Embodiments of this disclosure disclose a data processing method and apparatus for a blockchain, a device, a medium, and a product, which are applicable to the field of blockchain technologies. The method includes: packaging a first object operation transaction submitted by a first service object and a second object operation transaction submitted by a second service object in a to-be-assembled transaction pool to obtain an initial on-chain transaction, both the second service object and the first service object being off-chain registered objects; performing on-chain signing processing on the initial on-chain transaction by using private key information of a service providing object, and constructing a target on-chain transaction based on on-chain transaction signature information and transaction parameters in the initial on-chain transaction; and transmitting, when the service providing object is an on-chain registered object, the target on-chain transaction to a consensus node associated with a blockchain.