Abstract: Provided are a time domain resource allocation method and apparatus. The method includes the following operations. A terminal acquires at least one of first information including search space configuration information, control resource set (CORESET) configuration information, and a bandwidth part type. A PDSCH time domain resource allocation table is subsequently determined according to the first information and a multiplexing pattern between a synchronization signal/physical broadcast channel block (SSB) and a CORESET.

Abstract: A method, an electronic device, and a computer program product for generating a three-dimensional scene are provided in embodiments of the present disclosure. The method may include obtaining source image features from a plurality of two-dimensional source images associated with the three-dimensional scene to be generated. The method may further include obtaining editing features from an editing instruction input by a user for the three-dimensional scene, each of the editing features respectively forming a feature pair with each of the source image features. Furthermore, the method may include updating the source image features by maximizing a correlation coefficient of each of the feature pairs, and generating the three-dimensional scene based at least on the updated source image features. Embodiments of the present disclosure can realize arbitrary editing of a three-dimensional scene, thus enhancing the experience of human-computer interaction.

Abstract: A method includes generating a feature map of a second resolution for an input image of a first resolution, the first resolution being less than the second resolution. The method further includes generating a feature map of the second resolution and a feature map of the first resolution through a first residual-based dense back projection (RDBP) network. In addition, the method further includes generating a feature map of the second resolution and a feature map of the first resolution through a second RDBP network, the first RDBP network and the second RDBP network respectively including a downsampling back projection layer, an upsampling back projection layer, and an attention layer. The method further includes generating an output image of the second resolution based on the feature maps of the second resolution and the feature maps of the first resolution generated through the first RDBP network and the second RDBP network.

Abstract: Embodiments of the present disclosure relate to a method, an electronic device, and a computer program product for processing a virtual avatar. The method includes generating an image feature of the virtual avatar based on a plurality of image blocks of the virtual avatar and corresponding positions of the plurality of image blocks in the virtual avatar. The method further includes generating, based on a watermark to be added to the virtual avatar, a text feature associated with text of the watermark. The method further includes generating a watermarked virtual avatar based on the image feature and the text feature, wherein the watermark is invisible to human beings and identifies an identity of a user of the virtual avatar in a metaverse. Through embodiments of the present disclosure, identification of a virtual avatar, illustratively for verification and/or tracking purposes can be achieved without affecting the appearance of the virtual avatar.

Abstract: Embodiments of the present disclosure relate to a method, a device, and a computer program product for processing data. The method includes determining, based on acquired text, character features for a group of characters in the text and text features for the text. The method further includes determining initial visual features for the text based on the text features. The method further includes determining target visual features for the text based on the initial visual features, the character features, and the text features. The method further includes generating a target image corresponding to the text based on the target visual features. Through the method, the accuracy of conversion between text and an image is improved, the data processing efficiency is improved, and the data compression efficiency is further improved.

Abstract: Embodiments of the present disclosure relate to a method, an electronic device, and a computer program product for generating a target object. The method includes upsampling a first feature of an input point cloud. The method further includes determining a reference feature of a reference point cloud having a predetermined shape. The method further includes determining a second feature based on the upsampled first feature and the reference feature. The method further includes generating a three-dimensional target object based on the second feature and the input point cloud, wherein the target object has a fitted curved surface, and the target object has a greater number of points than the input point cloud. With embodiments of the present disclosure, a point cloud of the target object can be made denser, and the number of points can be increased, thereby achieving a more accurate three-dimensional reconstruction of the target object.

Abstract: Methods, apparatus, and processor-readable storage media for automatically processing user request data using artificial intelligence techniques are provided herein. An example computer-implemented method includes generating, using a chatbot during a communication session with a user, answers to user requests by processing the user requests using a first set of artificial intelligence techniques associated with the chatbot; generating knowledge base-related predictions associated with the user requests by processing the user requests using a second set of artificial intelligence techniques associated with a knowledge base; calculating at least one score associated with at least a portion of the answers and the user requests based on qualifying values computed in connection with at least one of generating the answers and generating the knowledge base-related predictions; and performing one or more automated actions based on the at least one calculated score.

Abstract: Embodiments of the present disclosure relate to a method, an electronic device, and a computer program product for processing a target object. The method includes acquiring an initial non-video feature vector on the basis of at least one input of a received speech input and text input. The method further includes taking, in response to not receiving a video input, a default feature vector as an initial video feature vector corresponding to the video input. The method further includes generating a video feature, a speech feature, and a text feature on the basis of the initial non-video feature vector and the initial video feature vector. The method further includes generating a processing parameter for a target object on the basis of the video feature, the speech feature, and the text feature, wherein the processing parameter includes at least one of an emotion parameter, an attribute parameter, and a pose parameter.

Abstract: Embodiments of the present disclosure relate to a method, a device, and a computer program product for rendering an image. The method includes determining, based on a coordinate value of a target point in a target scenario and a viewing direction for the target point, a rendering parameter for the target point. The method further includes adjusting the rendering parameter based on the viewing direction and by performing an upsampling operation on the rendering parameter. The method further includes rendering an image for the target scenario based on the adjusted rendering parameter. By means of the method, resources required by processing of image data are reduced; the image data processing speed is increased; and fast rendering of a high-resolution image can be achieved.

Abstract: A method, an electronic device, and a computer program product for video processing are provided in embodiments of the present disclosure. The method generates an avatar image using a reference image and image data for a first frame in a video stream, and generates an avatar video using the avatar image and image data, audio data, and text data in the video stream. Through this solution, a user-defined avatar video adapted to a user of a real video and actions thereof can be generated more accurately and with high quality.

Abstract: Embodiments of the present disclosure relate to a method, a device, and a computer program product for generating data. The method includes obtaining a multi-modality embedding by encoding multi-modality data, the multi-modality data comprising text data and image data. The method further includes obtaining a table embedding by encoding table data associated with the multi-modality data. The method further includes generating a condition embedding based on the multi-modality embedding and the table embedding. The method further includes generating multi-modality table data based on the condition embedding. In this way, it is possible to combine table data generation with multi-modality learning, which improves the characterization capability of the generated data and makes the generated data have sufficient information to describe a real scenario. At the same time, it is possible to reduce the model configuration cost and save computational and storage resources.

Abstract: Embodiments of the present disclosure relate to a method, a device, and a computer program product for image processing. The method includes determining a group of composite images, a composite image in the group of composite images being composited from images of the same type in a plurality of images. The method further includes determining an image quality of an acquired target image based on the group of composite images. The method further includes processing the acquired target image based on the image quality. Through the method, the storage and management of image data are improved, the effective utilization rate of data is improved, and the consumption of resources is reduced.

Abstract: Embodiments of the present disclosure relate to a method, an electronic device, and a computer program product for video reconstruction. The method for video reconstruction includes: receiving a video segment comprising a plurality of image frames. The method further includes: determining an audio segment corresponding to the video segment. The method further includes: acquiring a plurality of mask maps corresponding to the plurality of image frames, respectively. The method further includes: reconstructing the video segment based on the audio segment, the plurality of image frames, and the plurality of mask maps.

Abstract: Embodiments of the present disclosure relate to a method, an electronic device, and a computer program product for rendering a target scene. The method includes acquiring from a server rendering data including a point cloud and a color of the target scene. The method further includes determining a pose used for rendering the target scene at user equipment. The method further includes rendering the target scene on the basis of the rendering data and the pose, so as to show the target scene in the pose. In embodiments of the present disclosure, a rendering effect on the target scene can be improved, and the rendering speed is higher.

Abstract: In an illustrative embodiment, a method is disclosed for generating an image from fMRI data and EEG data. The method includes extracting a first feature map of the fMRI data, the first feature map being multidimensional data having a temporal dimension related to a sample collection time of the fMRI data, and converting the first feature map based on the temporal dimension of the first feature map and a first attention model. The method further includes extracting a second feature map of the EEG data, the second feature map being multidimensional data having a spatial dimension related to an electrode for collecting the EEG data, and converting the second feature map based on the spatial dimension of the second feature map and a second attention model. The method further includes generating an image based on the converted first feature map and the converted second feature map.

Abstract: Embodiments of the present disclosure relate to a method, an electronic device, and a computer program product for processing point clouds. The method includes performing upsampling on a first feature of a first point cloud of a target object. The method further includes determining a reference feature of a second point cloud of a reference object. The method further includes determining a second feature based on the first feature subjected to upsampling and the reference feature. The method further includes generating a third point cloud of the target object based on the second feature and the second point cloud of the reference object, where the third point cloud has a larger number of points than the first point cloud. Through embodiments of the present disclosure, a point cloud of the target object can be made denser, with increased accuracy, thereby providing a more detailed description of the target object.

Abstract: Embodiments of the present disclosure provide a method and an electronic device for point cloud processing. The method includes: obtaining a first point cloud based on an input point cloud, a point number of the first point cloud being greater than a point number of the input point cloud; obtaining a first group of point clouds based on the first point cloud, the first group of point clouds including a plurality of point clouds; obtaining a second group of point clouds based on the input point cloud and the first group of point clouds, the second group of point clouds including a plurality of point clouds; and obtaining a target point cloud based on the first point cloud and the second group of point clouds, a point number of the target point cloud being greater than the point number of the input point cloud.

Abstract: An online geometric/thermal error measurement and compensation system for computer numerically controlled (CNC) machine tools belonging to the technical field of error testing and compensation of CNC machine tools. The online CNC machine tool geometric/thermal error measurement and compensation system includes two parts: the hardware platform and the measurement and compensation software. The hardware platform includes a unidirectional acceleration sensor, a precision integrated circuit (IC) temperature sensor, a multi-channel temperature data collector, and a geometric/thermal error measurement and compensation host. The error measurement and compensation software runs in the geometric/thermal error measurement and compensation host and realizes testing and compensation of geometric and thermal errors in machine tools, which are communicated to the FANUC CNC system.

Abstract: An online geometric/thermal error measurement and compensation system for computer numerically controlled (CNC) machine tools belonging to the technical field of error testing and compensation of CNC machine tools. The online CNC machine tool geometric/thermal error measurement and compensation system includes two parts: the hardware platform and the measurement and compensation software. The hardware platform includes a unidirectional acceleration sensor, a precision integrated circuit (IC) temperature sensor, a multi-channel temperature data collector, and a geometric/thermal error measurement and compensation host. The error measurement and compensation software runs in the geometric/thermal error measurement and compensation host and realizes testing and compensation of geometric and thermal errors in machine tools, which are communicated to the FANUC CNC system.

Abstract: A method for the rapid detection of the linear axis angular error of an NC machine tool, belongs to the technical field of NC machine tool testing. Firstly, the measuring device is mounted on the linear axis. Then, the linear axis moves at three different speeds at a constant speed, and the upper measurement system automatically performs multi-channel acquisition and storage of the motion measurement's point measurement data. Then, based on the same geometric error signal, it is decomposed into the different frequency components, and the measurement angle error is filtered at the different speeds. Finally, the measurement angle errors at the three speeds after filtering are superimposed to complete the rapid measurement of the linear axis angular error of the machine tool. The measurement efficiency is high and data processing capability is strong.