Abstract: In a method for fabricating an air bridge, an air bridge brace structure is formed on a substrate. A continuous air bridge material layer is formed over the air bridge brace structure and the substrate. One or more openings are formed in the continuous air bridge material layer to reveal portions of the air bridge brace structure. A bridge brace material of the air bridge brace structure is removed through the one or more openings to obtain the air bridge. The air bridge includes the substrate and an air bridge structure that is disposed on the substrate. The air bridge structure includes the one or more openings. The one or more openings includes a first opening configured to pass through an etchant used to remove the bridge brace material. The one or more openings includes a second opening configured to pass through the bridge brace material removed by the etchant.

Abstract: The present disclosure discloses a method and apparatus for simulating a quantum circuit, a computer device, a storage medium, and a program product. The method includes: acquiring a polynomial by converting a unitary coupled-cluster (UCC) factor, wherein: an exponential part of the UCC factor comprises an anti-hermitian excitation operator G, and the polynomial comprises a linear term of the G and a quadratic term of the G; acquiring N UCC factors for constructing the UCC quantum circuit, N being an integer greater than 1; acquiring a wave function for representing a quantum state of an object; and obtaining a result wave function by performing operation in the form of the polynomial for each UCC factor in the N UCC factors on the wave function, wherein the result wave function represents the quantum state of the object after quantum simulation with the UCC quantum circuit.

Abstract: A video bitstream including coded information of a current block in a current picture is received. The current block is divided into a plurality of subblocks based on a region division shape of a plurality of region division shapes that is associated with an intra prediction mode of the current block. A weight set is determined for each of the plurality of subblocks, where the weight set includes a first weight for an intra prediction of the respective subblock and a second weight for an inter prediction of the respective subblock. Each of the plurality of subblocks is reconstructed based on the weight set, the intra prediction, and the inter prediction that are associated with the respective subblock.

Abstract: An information display method is provided. In the method, a first virtual object of a plurality of virtual objects in a first level of a chess game is displayed. The first virtual object is associated with a first user account. When a number of the plurality of virtual objects of the first level reaches a preset number, a first voucher and a second virtual object of a second level are displayed. The second virtual object is synthesized based on the preset number of the plurality of virtual objects. At least two candidate virtual objects are displayed when the first voucher is redeemed. When one of the at least two candidate virtual objects is selected by the first user, the selected candidate virtual object is displayed. The selected candidate virtual object is obtained by the first user account.

Abstract: Aspects of the disclosure provide a method and an apparatus for video coding. In some examples, the apparatus includes processing circuitry for video encoding. The processing circuitry selects a resolution from a set of resolutions that includes a 1-integer-pel resolution and a 4-integer-pel resolution. A current block is encoded with an intra block copy mode based on the selected resolution. The processing circuitry determines a block vector of the current block. The processing circuitry determines a block vector difference of the current block based on the block vector and a block vector predictor of the current block. The block vector difference is in the selected resolution. The processing circuitry encodes prediction information indicating the selected resolution and the block vector difference.

Abstract: This disclosure relates to a data processing method and apparatus, which may be applied to the field of blockchains to address low stability of a data processing process in a blockchain system. The method includes: obtaining status information of each of the slave nodes, the status information comprising a communication connection status of the corresponding slave node and a status of a blockchain recorded by the slave node in the blockchain system; in response to the status information of a first slave node among the slave nodes meeting a freeze condition, generating and broadcasting a node freeze proposal; and in response to the master node reaching a consensus on the node freeze proposal with the slave nodes based on a consensus algorithm, performing data interaction with the slave nodes other than the first slave node before the recorded blockchains reach the frozen block height.

Abstract: A resource processing method, including: receiving a first cross-chain proof transmitted by a node on a first blockchain, the first cross-chain proof carrying a first resource transfer record that has been uploaded to the first blockchain, a plurality of first blocks existing in the first blockchain, a plurality of second blocks in one-to-one correspondence with the plurality of first blocks existing in the second blockchain; verifying validity of the first resource transfer record based on the feature tree root feature of each second block header in the second blockchain to obtain a first verification result; and in response to the first verification result indicating a pass of the verification, unlocking and transferring out a second resource determined according to the first resource, from a second preset account in the second blockchain that corresponds to the first preset account.

Abstract: A method of training an audio separation network is provided. The method includes obtaining a first separation sample set, the first separation sample set including at least two types of audio with dummy labels, obtaining a first sample set by performing interpolation on the first separation sample set based on perturbation data, obtaining a second separation sample set by separating the first sample set using an unsupervised network, determining losses of second separation samples in the second separation sample set, and adjusting network parameters of the unsupervised network based on the losses of the second separation samples, such that a first loss of a first separation result outputted by an adjusted unsupervised network meets a convergence condition.

Abstract: A method includes receiving a current picture, a first reference picture, and a second reference picture. The method includes obtaining a plurality of predefined weighting patterns, each weighting pattern being signaled as an index value and selecting a weighting pattern based on a predetermined condition. The method includes deriving a first weight to be applied to a first sub-block in the first reference picture and a second weight to be applied to a second sub-block in the second reference picture based on the index value corresponding to the selected weighting pattern. The method includes assigning the first weight to the first sub-block and the second weight to the second sub-block based on the selected weighting pattern. The method includes decoding the current block by a weighted bi-prediction based at least on the first sub-block weighted by the first weight and the second sub-block weighted by the second weight.

Abstract: This application provides a method for reconstructing a three-dimensional model, a method for training a three-dimensional reconstruction model, an apparatus, a computer device, and a storage medium. The method for reconstructing a three-dimensional model includes: obtaining an image feature coefficient of an input image; respectively obtaining, according to the image feature coefficient, a global feature map and an initial local feature map based on a texture and a shape of the input image; performing edge smoothing on the initial local feature map, to obtain a target local feature map; respectively splicing the global feature map and the target local feature map based on the texture and the shape, to obtain a target texture image and a target shape image; and performing three-dimensional model reconstruction according to the target texture image and the target shape image, to obtain a target three-dimensional model.

Abstract: A method, computer program, and computer system is provided for identifying a speaker in at text based work. Labeled and unlabeled instances corresponding to one or more speakers are extracted. Pseudo-labels are inferred for the extracted unlabeled instances based on the labeled instances. One or more of the unlabeled instances are labeled based on the inferred pseudo-labels.

Abstract: This disclosure is related to an image generation method and apparatus. The method includes: obtaining a first body image including a target body and a first clothes image including target clothes; transforming the first clothes image based on a posture of the target body in the first body image to obtain a second clothes image, the second clothes image including the target clothes, and a posture of the target clothes matching the posture of the target body; performing feature extraction on the second clothes image, an image of a bare area in the first body image, and the first body image to obtain a clothes feature, a skin feature, and a body feature respectively; and generating a second body image based on the clothes feature, the skin feature, and the body feature, the target body in the second body image wearing the target clothes.

Abstract: Systems and methods for encoding and decoding neural network data is provided. A method includes: obtaining an independent neural network with a topology; encoding the independent neural network with the topology such as to obtain a neural network representation (NNR) bitstream; and sending the NNR bitstream to a decoder, wherein the NNR bitstream includes a group of NNR units (GON) that represents the independent neural network with the topology, and the GON includes an NNR model parameter set unit, an NNR layer parameter set unit, an NNR topology unit, an NNR quantization unit, and an NNR compressed data unit.

Abstract: A method of depth map completion is described. A color map and a sparse depth map of a target scenario can be received. Resolutions of the color map and the sparse depth map are adjusted to generate n pairs of color maps and sparse depth maps of n different resolutions. The n pairs of color maps and the sparse depth maps can be processed to generate n prediction result maps using a cascade hourglass network including n levels of hourglass networks. Each of the n pair is input to a respective one of the n levels to generate the respective one of the n prediction result maps. The n prediction result maps each include a dense depth map of the same resolution as the corresponding pair. A final dense depth map of the target scenario can be generated according to the dense depth maps.

Abstract: Aspects of the disclosure provide methods and an apparatus including processing circuitry configured to receive workflow information of a workflow. The processing circuitry generates, based on the workflow information, the workflow to process input data. The workflow includes a first processing task, a second processing task, and a first buffering task. The first processing task is caused to enter a running state where a subset of the input data is processed and output to the first buffering task as first processed subset data. The first processing task is caused to transition to a paused state based on an amount of the first processed subset data in the first buffering task being equal to a first threshold. State information of the first processing task is stored in the paused state. Subsequently, the second processing task is caused to enter a running state where the first processed subset data is processed.

Abstract: Methods, apparatus, and computer readable storage medium for intra bi-prediction and multiple reference line intra prediction in video decoding. The method includes receiving, by a device, a coded video bitstream for a block. The method also includes determining, by the device, whether a single directional intra prediction or an intra bi-prediction applies to the block, based on mode information of the block, the mode information of the block comprising at least one of: a reference line index of the block, an intra prediction mode of the block, and a size of the block; in response to determining that the single directional intra prediction applies to the block, performing, by the device, the single directional intra prediction to the block; and in response to determining that the intra bi-prediction applies to the block, performing, by the device, the intra bi-prediction to the block.

Abstract: A method, device, and computer-readable medium for decoding an encoded video bitstream using at least one processor, including obtaining a first flag indicating that a conformance window is present in a current picture; based on the first flag indicating that the conformance window is present, obtaining a second flag indicating whether the conformance window is used for reference picture resampling; based on the second flag indicating that the conformance window is used for the reference picture resampling, determining a resampling ratio between the current picture and a reference picture based on a conformance window size of the conformance window; based on the second flag indicating that the conformance window is not used for the reference picture resampling, determining the resampling ratio based on a resampling picture size; and performing the reference picture resampling on the current picture using the resampling ratio.

Abstract: Neural network based substitutional end-to-end (E2E) image compression (NIC) being performed by at least one processor and includes receiving an input image to an E2E NIC framework, determining a step size of the input image indicating a learning rate of a training model, determining a substitute image based on the training model, encoding the substitute image in lieu of the input image to generate a bitstream, and mapping the substitute image to the bitstream to generate a compressed representation. Further, step size may be determined by a scheduler and change throughout the training of the training model. The image may also be split into patches for which a scheduler is assigned for each patch and each patch is encoded instead of the entire input image.

Abstract: A method, an apparatus and a storage medium for constructing a three-dimensional (3D) facial mesh using artificial intelligence is disclosed. The method includes: obtaining a facial point cloud of a target object; determining, through an expansion calculation, pixel coordinates on a facial texture image of the target object that correspond to 3D data points in the facial point cloud, as index information of the 3D data points; performing triangulation on pixels on the facial texture image to obtain triangulation information; constructing an initial 3D facial mesh according to the triangulation information, the index information, and the facial point cloud; determining a non-core region in the initial 3D facial mesh; smoothing the non-core region in the initial 3D facial mesh; and replacing the non-core region in the initial 3D facial mesh with the smoothed non-core region to obtain a 3D facial mesh of the target object.

Abstract: An information exchange method and a related apparatus include a game picture that may be displayed that includes a candidate skill region, a target skill determined based on a skill selection operation for the candidate skill region, a virtual joystick object displayed on the game picture, and when a movement operation for the virtual joystick object is detected, at least one skill generation position of the target skill is calculated based on the movement operation. A skill effect model of the target skill is generated at the at least one skill generation position when a cast operation for the virtual joystick object is detected. A user may control a plurality of skill effect model generation positions of a game skill through the virtual joystick object, so that precision of information exchange can be improved.