Abstract: Embodiments of this disclosure include a training method for an image processing model. In the method, parameters of an encoder in the image processing model are updated according to a to-be-replaced face in an original image, to configure the encoder to encode the to-be-replaced face to obtain a visual feature of the to-be-replaced face. Parameters of a decoder in the image processing model are updated according to the to-be-replaced face in the original image, to configure the decoder to perform decoding based on the visual feature of the to-be-replaced face. The parameters of the decoder are further updated according to a target face in a target image without changing the parameters of the encoder, to configure the decoder to perform decoding based on the visual feature of the to-be-replaced face and obtain a target face having the same visual feature as the to-be-replaced face.

Abstract: A coding block processing method includes receiving a bit stream, and determining, according to the bit stream, that a current coding block is coded in intra block copy mode, and that the current coding block overlaps a reference coding block. The method further includes, in response to the determination that the current coding block overlaps the reference coding block, determining that the current coding block is a merged block and partitioning the merged block into plural sub-blocks. The method further includes determining motion information of the plural sub-blocks based on one set of motion information indicated in the bit stream, such that the plural subblocks have the same motion information.

Abstract: A conference data processing method includes acquiring a first meeting list of meetings created by a user, meetings in the first meeting list having been created by the user through an instant messaging (IM) client. The IM client includes an interface for calling a software development kit (SDK) of a separate conference application implementing at least one of audio or video conferencing. The method further includes requesting, through a fusion server, a server of the conference application to create a second meeting list according to the first meeting list, and receiving, through the fusion server, the second meeting list transmitted by the server of the conference application. The second meeting list includes meetings that correspond respectively to the meetings in the first meeting list. The method further includes establishing an association relationship between a meeting in the first meeting list and a meeting in the second meeting list.

Abstract: A method for obtaining sensing data includes transmitting, by a network function element to a terminal device, sensing data request information comprising parameters for sensing and reporting data by the terminal device. The sensing data request information indicates, to the terminal device, to report sensing data to the network function element according to the parameters. The method further includes obtaining sensing data returned by the terminal device, the sensing data being transmitted by the terminal device according to the parameters indicated in the sensing data request information. The method further includes preprocessing, by the network function element, the sensing data and providing a result of the preprocessing to a server.

Abstract: A virtual interaction method including displaying a virtual scenario comprising a first virtual figure and a second virtual figure that participate in a battle game task, wherein the first virtual figure is controlled by a first device. The method further includes, in response to a trigger operation on the first device, displaying the first virtual figure and a target virtual figure performing an action directed to the second virtual figure together, wherein the target virtual figure is not controlled by the first device.

Abstract: A virtual object control method and apparatus, a terminal, and a storage medium. The method includes: displaying a virtual scene interface, the virtual scene interface including a first virtual object, second virtual objects, and ability controls; determining, in response to a first trigger operation on a first ability control, a target virtual object from the second virtual objects and according to the first trigger operation, and controlling the first virtual object to cast a first ability on the target virtual object; determining the target virtual object as an ability casting target corresponding to a second ability when a second trigger operation on a second ability control meets an ability continuous casting condition, the second trigger operation being triggered during ability casting of the first ability; and controlling the first virtual object to cast the second ability on the target virtual object.

Abstract: In a data processing method for a point cloud media, a media file of the point cloud media is obtained. The media file includes stream data of a plurality of point cloud frames and decoding indication information of each of the plurality of point cloud frames. The decoding indication information of each of the plurality of point cloud frames includes at least two attribute headers. Each of the at least two attribute headers includes attribute identifier information. The point cloud media is processed based on the stream data and the decoding indication information.

Abstract: A point cloud including a plurality of points is acquired. Each of the plurality of points includes N pieces of attribute information. N is a positive integer greater than 1. A to-be-coded value is determined for each of the N pieces of attribute information of a current point of the plurality of points based on the N pieces of attribute information of a point prior to the current point being encoded. The to-be-coded values of the N pieces of attribute information of the current point are encoded based on at least one of a selected encoder or a selected coding mode to obtain a code stream of the point cloud. The to-be-coded value for each of the N pieces of attribute information of the current point is encoded based on a respective one of the one or more encoders and a respective one of the one or more coding modes.

Abstract: A video encoding/decoding approach including generating a prediction vector candidate list according to displacement vectors of an encoded/decoded block whose reference frame is a current frame; selecting a prediction vector of a to-be-encoded/decoded current block from the prediction vector candidate list; and encoding/decoding the current block based on the prediction vector of the current block.

Abstract: A point cloud decoding method is provided. In the method, a target point cloud group of a plurality of point cloud groups is obtained. The target point cloud group includes at least one point. An attribute coding mode of the target point cloud group is determined. Prediction attribute information of each point in the target point cloud group is obtained based on attribute prediction of the respective point in the target point cloud group according to the attribute coding mode of the target point cloud group. Reconstruction residual information of each point in the target point cloud group is obtained based on attribute decoding of the respective point in the target point cloud group. Reconstruction attribute information of each point in the target point cloud group is determined according to the prediction attribute information and the reconstruction residual information of the respective point in the target point cloud group.

Abstract: A spectator interaction method includes displaying an interactive control for a first spectator account watching an online battle, the interactive control configured to trigger an interaction between the first spectator account and one or more spectator accounts currently watching the online battle. The method further includes displaying first interactive content in response to receiving a trigger operation on the interactive control. The method further includes displaying a quantity of spectator accounts corresponding to the first interactive content, the quantity of spectator accounts including accounts that have interacted with the first interactive content, and accounts that have interacted with second interactive content triggered by a second spectator account. The second interactive content being a same interactive content type as the first interactive content.

Abstract: The present disclosure provides an endoscopic image processing method and system, and a computer device. The method can include acquiring a current endoscopic image of a to-be-examined user, and predicting the current endoscopic image by using a deep convolutional network based on a training parameter. The training parameter can be determined according to at least one first endoscopic image and at least one second endoscopic image transformed from the at least one first endoscopic image, where the at least one endoscopic image corresponds to a human body part. The method can further include determining an organ category corresponding to the current endoscopic image. The method provided in the present disclosure can make a prediction process more intelligent and more robust, thereby improving resource utilization of a processing apparatus.

Abstract: A picture filtering method includes determining encoding information of a picture, the encoding information comprising classification information indicating one of an intra encoding mode or an inter encoding mode of the picture. The method further includes inputting the picture and the classification information indicating one of the intra encoding mode or the inter encoding mode into a general filtering model trained using deep learning, and obtaining a filtered picture based on the filtering model performing filtering on the picture based on the encoding information.

Abstract: An action recognition method includes: obtaining original feature submaps of each of temporal frames on a plurality of convolutional channels by using a multi-channel convolutional layer; calculating, by using each of the temporal frames as a target temporal frame, motion information weights of the target temporal frame on the convolutional channels according to original feature submaps of the target temporal frame and original feature submaps of a next temporal frame, and obtaining motion information feature maps of the target temporal frame on the convolutional channels according to the motion information weights; performing temporal convolution on the motion information feature maps of the target temporal frame to obtain temporal motion feature maps of the target temporal frame; and recognizing an action type of a moving object in image data of the target temporal frame according to the temporal motion feature maps of the target temporal frame on the convolutional channels.

Abstract: A method for matching audio clips includes: obtaining a first feature sequence corresponding to a first audio clip and a second feature sequence corresponding to a second audio clip; constructing a distance matrix, elements in the distance matrix representing respective distances between first positions in the first feature sequence and second positions in the second feature sequence; calculating a first accumulation distance between a start position and a target position in the distance matrix, and calculating a second accumulation distance between an end position and the target position in the distance matrix; and calculating a minimum distance between the first feature sequence and the second feature sequence based on the first accumulation distance and the second accumulation distance, and determining a degree of matching between the first audio clip and the second audio clip according to the minimum distance.

Abstract: A video decoding method includes: obtaining target type information of a target video upon receiving a play instruction of the target video, the target type information indicating a type of the target video; obtaining specified type information of a plurality of decoders configured in a terminal, the specified type information of the decoders indicating types of videos of which decoding is supported by the decoders; and determining, from the plurality of decoders by comparing the specified type information of the plurality of decoders with the target type information, a target decoder that supports decoding of the target video. The target video is decoded by using the target decoder to play a decoded video.

Abstract: Embodiments of this disclosure include an information processing method, an information processing apparatus, and non-transitory computer-readable storage medium. A first key frame that includes initial posture data corresponding to an initial posture of a target virtual character is obtained. Target posture data is determined by inputting the initial posture data and a target task to a policy network trained by reinforcement learning. An output of the policy network indicates the target posture data corresponding to a target posture. At least one force to be acted on at least one first joint of the target virtual character is determined according to the initial and the target posture data. A posture of the target virtual character is adjusted from the initial posture to the target posture by applying the at least one force on the at least one first joint to obtain a second key frame.

Abstract: An image processing method includes: obtaining DCE magnetic resonance images corresponding to a plurality of time points for a same detection target; determining average pixel grayscale values of images of a same lesion region in the DCE magnetic resonance images of the plurality of time points respectively; determining a time to peak according to the average pixel grayscale values corresponding to the plurality of time points; and generating a first-stage time-intensity image before the time to peak and a second-stage time-intensity image after the time to peak respectively according to the DCE magnetic resonance images and the time to peak. The first-stage time-intensity image and the second-stage time-intensity image are 3D images. A pixel grayscale value of each pixel in the first-stage time-intensity image and the second-stage time-intensity image represents a change rate of blood supply intensity and reflects a severity level of a lesion corresponding to the lesion region.

Abstract: This application discloses a method for determining an implantation location of recommendation information performed at a computer device. The method includes: acquiring a target video; acquiring, according to a scene change status of the target video, a target video frame being used for location detection; performing image recognition on the target video frame to obtain masking information of the target video frame including a first region of an object of a target type in the target video frame; and determining an implantation location of recommendation information in the target video frame based on the first region. Image recognition processing is performed on the target video frame to obtain the masking information of the target video frame, so as to determine the implantation location in the target video frame on the basis of the first region corresponding to the object of the target type in the target video frame.

Abstract: A data transmission method includes: displaying a target message in a session interface; in response to a trigger operation on the target message, outputting a resource transmission interface including an object display region and an icon display region; and the object display region including an object identifier of at least one transmission object, and the icon display region including a message icon corresponding to the target message; moving the message icon from the icon display region to the object display region according to a moving operation on the message icon; and transmitting, in response to the message icon being moved to the object display region, the data resource to a target transmission object of the at least one transmission object in the object display region, the target transmission object being determined according to an ending position of a movement track of the message icon corresponding to the moving operation.