Abstract: A method of forming a volumetric effect on a game map of a video game is provided. In the method, a variable density volume of the game map is determined based on a mesh of the game map and a bounding box. The variable density volume includes the volumetric effect. The variable density volume is sliced into a plurality of texture layers. Each of the plurality of texture layers includes information associated with at least one of the volumetric effect or the mesh. An interaction between a virtual object on the game map and the volumetric effect is determined based on movement of the virtual object. The volumetric effect is rendered based on a cut out of the virtual object in the variable density volume and the determined interaction.

Abstract: A method is provided for terminating movement of a first unit in a video game. The method includes obtaining a target destination on a game map for the first unit. The method includes controlling the first unit to move towards the target destination. The method includes determining a number of units in a destination area of the game map, the destination area being based on a current position of the first unit on the game map and a destination position of the target destination on the game map. The method includes determining whether to stop the movement of the first unit towards the target destination before the first unit reaches the target destination based on the destination area and the number of units in the destination area. The method includes stopping the first unit based on a determination to stop the movement of the first unit towards the target destination.

Abstract: An obstacle detection method can improve the accuracy of determining a relative positional relationship between two or more obstacles that are obstructed or obscured during automated driving. A road scene image of a road where a target vehicle is located is acquired. Obstacle recognition is performed to obtain region information and depth-of-field information corresponding to each obstacle in the road scene image. Target obstacles in an occlusion relationship and a relative depth-of-field relationship between the target obstacles are determined. A ranging result of each obstacle is acquired using a ranging apparatus corresponding to the target vehicle. An obstacle detection result of the road is determined based on the relative depth of field relationship between the target obstacles and the ranging result of each obstacle, thereby improving the accuracy of determining a positional relationship of obstructed or obscured obstacles during automated driving.

Abstract: An unmanned vehicle control method includes acquiring a delivery request for an item, the delivery request comprising delivery information of the item, and determining, according to the delivery information, predicted travelling data associated with delivering the item and at least one of network coverage or network connection quality associated with the predicted travelling data. The method further includes allocating network resources according to the at least one of the network coverage or the network connection quality of the predicted travelling data, and generating a remote driving control instruction according to the predicted travelling data. The method further includes transmitting the remote driving control instruction to an unmanned vehicle using the allocated network resources, so as to cause the unmanned vehicle to drive based on the remote driving control instruction, the unmanned vehicle being configured to transport the item.

Abstract: A method includes segmenting a multidimensional media stream into a plurality of segments of multidimensional media in a multidimensional space; representing each segment of the plurality of segments of multidimensional media using a respective sequence vector, the respective sequence vector comprising one or more predefined multidimensional metadata, wherein the predefined multidimensional metadata includes a startcode that is an identical unique code point and a sequence number, wherein each segment includes the identical unique code point; and deriving a network based media processing (NBMP) workflow based on the respective sequence vector of each segment of the plurality of segments.

Abstract: A method is provided. The method includes generating, by a 5th generation media streaming (5GMS) application provider, an edge configuration resource including at least one edge enabler client (EEC) capability specification, transmitting, by the 5GMS application provider, a request for provisioning an edge application server (EAS) to operate as a 5GMS application server (AS), the request including the edge configuration resource, and selecting, by the 5GMS application provider, the EAS to operate as the 5GMS AS based on the EAS being capable of performing the at least one EEC capability specification included in the edge configuration resource.

Abstract: In a network connection method, a first management frame for performing a network connection is received from a to-be-accessed Internet of things device. The first management frame includes device attribute information of the Internet of things device. The device attribute information of the Internet of things device is transmitted to a terminal device connected to the network device. A target verification result of a validity verification of the Internet of things device that is performed in response to the device attribute information is received from the terminal device. A second management frame that includes network attribute information of the network device is generated based on the target verification result, the target verification result indicating that the Internet of things device is valid. The second management frame is transmitted to the Internet of things device.

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: 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 data migration method includes: obtaining, by a first node, a first route assignment table; receiving, by the first node, a first instruction; obtaining, by the first node by using the first route assignment table, a first partition identity (ID) based on a first primary key ID carried in the first instruction; determining, by the first node, a second node based on the first partition ID; and transmitting, by the first node, first data uniquely identified by the first primary key ID to the second node.

Abstract: A method and apparatus for adaptive neural image compression with smooth quality control by meta-learning includes receiving an input image and a target quality control parameter; generating quality-adaptive weight parameters of an encoding neural network using shared encoding parameters and adaptive encoding parameters; and encoding the input image, based on the target quality control parameter, using the encoding neural network with the quality-adaptive weight parameters, to generate a compressed representation.

Abstract: A method includes: in response to detecting a communication connection between the electronic device and the user equipment, obtaining a user instruction transmitted to the user equipment, the user instruction including at least one preset parameter for setting an interface feature of a target logical interface on the electronic device. The target logical interface is used for verifying an identity of a user. The method includes generating the target logical interface, by setting the interface feature based on the user instruction on the electronic device; obtaining verification information of a user; collecting a face image of the current user through the target logical interface; and verifying an identity of the current user based on the face image and the verification information.

Abstract: A method comprising segmenting an input symmetry mesh into multiple non-connected UV segments; partitioning at least one UV segment via a plane that partitions the at least one UV segment into a first side and a second side; reorganizing the plurality of vertices included in the first side of the at least one UV segment; perform a 2D symmetry detection on the at least one UV segment to find a symmetry transform; determining a predicted vertex for each vertex on the second side of the at least one UV segment based on the symmetry transform of a corresponding vertex on the first side of the at least one UV segment to find a predicted vertex on the first side of the at least one UV segment; and encoding a bitstream that comprises at least the vertices within the first side of the at least one UV segment.

Abstract: This disclosure relates generally to encoding and decoding of 3-dimensional (3D) mesh and specifically to encoding and decoding order and dependency between 3D positions of 3D vertices and 2D positions of 2D texture coordinates of a 3D mesh. In particular, the various embodiments in this disclosure provide a novel method and device to enhance lossless compression of 3D mesh models. The disclosed method and device prioritize encoding texture coordinates before encoding 3D positions. The disclosed method and device further employ angle-preserving position prediction. The disclosed approaches aim to optimize the compression process of 3D meshes by leveraging an inherent correlation between 3D structures and their corresponding 2D texture mappings.

Abstract: A method and apparatus comprising computer code configured to cause a processor or processors to determine capabilities of an augmented reality (AR) device, the capabilities indicating, as part of the AR device serving as a split rendering client (SRC), any of an audio encoder or decoder of the AR device and a video encoder or decoder of the AR device; obtain AR data of a media component of at least one of audio and video based on a request signaling the capabilities of the AR device to a server, acting as a split rendering server (SRS) for split rendering of the media component between the SRS and the SRC, providing the AR data; and process the AR data based on the capabilities of the AR device signaled to the SRC.

Abstract: A method and apparatus comprising computer code configured to cause a processor or processors to receive an input question to the LLM, the LLM comprising a pretrained model and an aligned model, determine whether a portion of an unfinished response to the input question is factual, and answer the input question by at least adding to the unfinished response by a token-level router routing either to the pretrained model, based on determining that the portion is factual, or routing to the aligned model, based on determining that the portion is not factual.

Abstract: A video bitstream is received. The video bitstream includes coded information of a current block in a current picture and of a plurality of reference pictures of the current picture in a reference list. A plurality of intermediate vectors associated with one of the plurality of reference pictures is determined. The plurality of intermediate vectors includes an initial vector and a plurality of intermediate motion vectors (MVs). The initial vector is associated with the current picture. Each of the plurality of intermediate MVs is defined between two respective reference pictures of the plurality of reference pictures. A candidate motion vector predictor (MVP) is determined for the current block based on a sum of the plurality of intermediate vectors. The current block is reconstructed based on an MVP candidate list that includes the candidate MVP.

Abstract: In a method for video decoding, a target sub-block on which entropy decoding is to be performed is obtained, from a bitstream, based on partitioning a coding block according to a residual block corresponding to the coding block. Transform sub-block information about at least one transform sub-block is obtained, the at least one transform sub-block obtained by partitioning the target sub-block. An inverse quantization coefficient sub-block corresponding to the at least one transform sub-block is obtained based on entropy decoding and inverse quantizing the at least one transform sub-block with the transform sub-block information about the at least one transform sub-block. A reconstructed residual corresponding to the coding block is generated based on inverse transforming the inverse quantization coefficient sub-block corresponding to the at least one transform sub-block, a residual of an area other than the target sub-block in the coding block being inferred to be zero.

Abstract: In a method for data processing, when media data and a user viewing the media data simultaneously satisfy a media reference condition, a media reference control is displayed in a media interaction platform configured to display the media data and different from a subprogram platform configured to maintain a subprogram. A subprogram selection list associated with the user is displayed in the media interaction platform based on a trigger operation on the media reference control. An external credential for the media data that is configured for the user to reference the media data to a target subprogram that has permission to display the media data is obtained based on a user performing a confirmation operation with the subprogram selection list.

Abstract: Aspects of the disclosure provide methods and apparatuses for video coding. In some examples, an apparatus includes processing circuitry. The processing circuitry obtains prediction information of a first block in a picture from a coded video bitstream, and generates reconstructed samples of the first block according to the prediction information and one of bi-directional prediction and uni-directional prediction. The processing circuitry adds motion information and a bi-prediction weight index of a History-based Motion Vector Prediction (HMVP) candidate to an HMVP list based on the prediction information of the first block and whether the first block is coded according to the bi-directional prediction or the uni-directional prediction. Further, the processing circuitry generates reconstructed samples of a second block in the picture based on a plurality of candidates that includes the HMVP candidate.