11249 results about "Bitstream" patented technology

By implementing a new bitstream for a Delta-Quantization Parameter (DQP), a decoder is able to implement parallel decoding of multiple coding units within a largest coding unit. In some embodiments, the DQP is placed immediately after the mode information of the first coding unit. In some embodiments, the DQP is placed after the mode information of the first non-skipped coding unit. In some embodiments, the DQP is placed after the first non-zero coded block flag.

A computer-implemented method for decoding a coded mesh bitstream of a dynamic mesh representing three-dimensional content includes that: geometry information of the dynamic mesh is reconstructed from a geometry component bitstream in the coded mesh bitstream, the reconstructed geometry information includes data specifying vertices of the dynamic mesh; connectivity information of the dynamic mesh is reconstructed from a connectivity component bitstream in the coded mesh bitstream, the reconstructed connectivity information includes data specifying faces of the dynamic mesh; the reconstructed connectivity information is refined based on the reconstructed geometry information to generate refined connectivity information by at least dividing a face specified by the reconstructed connectivity information into two faces based on a vertex specified in the reconstructed geometry information; the dynamic mesh is reconstructed based on the reconstructed geometry information and the refined connectivity information; and the reconstructed dynamic mesh is caused to be rendered for display.

A device may be configured to compress feature data according to one or more of the techniques described herein. In one example, feature data may be compressed by using residual encoding to enhance the feature data by removing redundancies. Enhanced feature data may be spatially down sampled and the number of channels of the enhanced feature data may be reduced by applying a 2D convolution operation. A heatmap based on the reduced enhanced feature data may be generated. The reduced enhanced feature data may be scaled using the generated heatmap. The scaled reduced enhanced feature data may be entropy encoded to generate a bitstream.

Systems and methods are described for video coding using generalized bi-prediction. In an exemplary embodiment, to code a current block of a video in a bitstream, a first reference block is selected from a first reference picture and a second reference block is selected from a second reference picture. Each reference block is associated with a weight, where the weight may be an arbitrary weight ranging, e.g., between 0 and 1. The current block is predicted using a weighted sum of the reference blocks. The weights may be selected from among a plurality of candidate weights. Candidate weights may be signaled in the bitstream or may be derived implicitly based on a template. Candidate weights may be pruned to avoid out-of-range or substantially duplicate candidate weights. Generalized bi-prediction may additionally be used in frame rate up conversion.

A method implemented by a video coding apparatus. The method includes applying a neural network (NN) filter to an unfiltered sample of a video unit to generate a filtered sample. The NN filter includes an NN filter model generated based on partitioning information of the video unit. Usage of the NN filter is indicated by one or more syntax elements in a bitstream. A conversion is performed between a video media file and a bitstream based on the filtered sample.

A video decoding method, including: obtaining a first index by decoding a bitstream, where the first index is used to indicate a first combination, the first combination includes a weight derivation mode and K prediction modes, and K is a positive integer greater than 1; determining a first weight derivation mode and K first prediction modes included in the first combination according to the first index; and obtaining a prediction value of a current block by predicting the current block according to the first weight derivation mode and the K first prediction modes.

The disclosure relates to a data processing method and a related device for point cloud media. The method includes: obtaining a media file of point cloud media, the media file comprising a point cloud bitstream and cross-attribute dependency indication information of the point cloud media, and the cross-attribute dependency indication information being for indicating an encoding and decoding dependency relationship between attribute data in the point cloud bitstream; and decoding the point cloud bitstream based on the cross-attribute dependency indication information to present the point cloud media.

The invention discloses a semantic communication method for adaptive coding of a semantic source channel under a parallel channel. The method comprises the following steps: S1, constructing a communication model for adaptive coding of the semantic source channel under the parallel channel; s2, at a sending end, encoding semantic information source samples in (X, S), distributing bit streams after encoding each semantic information source sample to an independent channel for transmission, and adopting K channel encoders with different channel rates to protect respective bit streams so as to resist channel errors; s3, at a receiving end, decoding the received signals by using K channel decoders, combining the received signals into a single serial flow, and decoding the single serial flow by using a semantic source decoder based on a deep neural network; s4, determining a source rate and prior information under any given deep neural network model; and S5, constructing an optimization problem, and performing joint optimization of the deep neural network parameter phi and the resource allocation variable # imgabs0 #. According to the invention, resource allocation optimization in a parallel Gaussian channel scene is realized.

A method for processing media data is disclosed. In an embodiment, the method includes determining a value of a neural-network post-filter characteristics (NNPFC) purpose (nnpfc_purpose) in a NNPFC supplemental enhancement information (SEI) message, wherein the nnpfc_purpose is configured to be set to include output picture size downsampling, and wherein at least one of (1) an output picture width is not equal to an input picture width and (2) an output picture height is not equal to an input picture height; and performing a conversion between a visual media data and a bitstream based on the nnpfc_purpose.

Methods, systems, and bitstream syntax are described for video coding and decoding using source picture timing information which is captured by an encoder and is signaled as metadata to a decoder to assist in decoding. The proposed methods include example syntax for signaling source picture timing metadata as supplemental enhancement information (SEI) messaging for both single-layer and multi-layer video sequences.

Methods, systems, and metadata for video communications using generative face video (GFV) are described. In encoder, a GFV bitstream is generating comprising multiplexed coded face video pictures and GFV metadata. Using supplemental enhancement information (SEI), a GFV SEI message comprises syntax elements describing face features and at least one or more of: presence of a single or multiple faces, spatial sampling, temporal sampling, primary code picture characteristics and driving-picture handling, background handling, persistence of SEI, and compression parameters for face features. In a decoder, the decoder combines information extracted from the GFV metadata and the decoded face video pictures to generate a reconstructed output video.

A point cloud data transmission method according to embodiments may comprise the steps of: encoding point cloud data; and transmitting a bitstream comprising the point cloud data. A point cloud data reception method according to embodiments may comprise the steps of: receiving a bitstream comprising point cloud data; and decoding the point cloud data.

A method for learning-based point cloud geometry compression includes: given a source point cloud, regressing an aligned mesh that is driven by a set of parameters from a deformable template mesh, quantizing the set of parameters into a parameter bitstream, generating an aligned point cloud from the quantized parameters by mesh manipulation and mesh-to-point-cloud conversion, extracting features from both the source point cloud and the aligned point cloud based on sparse tensors including coordinates and features, the coordinates being encoded into a coordinate bitstream, warping the features of the aligned point cloud onto the coordinates of the source point cloud, obtaining residual features through feature subtraction, processing the residual features using an entropy model into a residual feature bitstream, and obtaining a reconstructed point cloud by processing the parameter bitstream, the coordinate bitstream and the residual feature bitstream.

A point cloud data transmission method according to embodiments may comprise the steps of: encoding point cloud data; and transmitting a bitstream including the point cloud data. A point cloud data receiving method according to embodiments may comprise the steps of: receiving a bitstream including point cloud data; and decoding the point cloud data.

Disclosed are methods and apparatuses for decoding an image. A method includes receiving a bitstream obtained by encoding the image; dividing a first coding block into a plurality of second coding blocks; generating a prediction block of a second coding block based on syntax information obtained from the bitstream; and reconstructing the second coding block based on the prediction block and a residual block of the second coding block, the residual block being obtained by performing a dequantization and an inverse-transform on quantized transform coefficients from the bitstream. The first coding block has a recursive division structure. The first coding block is divided based on at least one of a quad tree division, a binary tree division or a triple tree division.

A point cloud data transmission method according to embodiments may comprise the steps of: encoding point cloud data; and transmitting a bitstream including the point cloud data. A point cloud data reception method according to embodiments may comprise the steps of: receiving the bitstream including the point cloud data; and decoding the point cloud data.

A method and apparatus comprising computer code configured to cause a processor or processors to obtain, from a bitstream, a mesh representing an encoded volumetric data of at least one three-dimensional (3D) visual content; partition a plurality of vertices of the mesh into a plurality of groups; and decode the encoded volumetric data by predicting the vertices in each group of the plurality of groups based on a plurality of traversal orders depending on an adaptive reference vertex of the vertices, and the plurality of traversal orders includes a first order from the adaptive reference vertex to a first alternative reference vertex of the vertices, and wherein the plurality of traversal orders includes a second order from the adaptive reference vertices to a second alternative reference vertex of the vertices.

Devices, systems, and methods for encoding and decoding digital video using a lookup table (LUT) containing motion candidates are described. In a representative aspect, a method of video processing includes: maintaining one or more tables, wherein at least one of the one or more tables is associated with one or more entries; deriving a second set of motion candidates based on a first set of motion candidates in the at least one table; and performing a conversion between a current block of a video and a bitstream representation of the video based on the second set of motion candidates.

An apparatus configured to: obtain a first bitstream, wherein the first bitstream is encoded according to a first coding method; obtain at least one second bitstream, wherein the at least one second bitstream is encoded according to a second coding method; and generate an encapsulated file, wherein a track of the encapsulated file comprises the first bitstream and sample auxiliary information of the track comprises the at least one second bitstream, wherein the encapsulated file comprises, at least: an indication that the first bitstream is encapsulated in samples of the track, and an indication that the at least one second bitstream is encapsulated in the sample auxiliary information of the track.

A point cloud data transmission method according to embodiments may comprise the steps of: encoding point cloud data; and transmitting a bitstream including the point cloud data. In addition, a point cloud data transmission device according to embodiments may comprise: an encoder which encodes point cloud data; and a transmitter which transmits a bitstream including the point cloud data.

A device for decoding encoded mesh data is configured to receive, in a bitstream of the encoded mesh data, one or more syntax elements; determine an offset value based on the one or more syntax elements; determine a set of transform coefficients; apply the offset to the set of transform coefficients to determine a set of updated transform coefficients; inverse transform the set of updated transform coefficients to determine a set of displacement vectors; and determine a decoded mesh based on the set of displacement vectors.

A computer-implemented method for lossy image or video compression, transmission and decoding, the method including the steps of: (i) receiving an input image at a first computer system; (ii) encoding the input image using a first trained neural network, using the first computer system, to produce a latent representation; (iii) quantizing the latent representation using the first computer system to produce a quantized latent; (iv) entropy encoding the quantized latent into a bitstream, using the first computer system; (v) transmitting the bitstream to a second computer system; (vi) the second computer system entropy decoding the bitstream to produce the quantized latent; (vii) the second computer system using a second trained neural network to produce an output image from the quantized latent, wherein the output image is an approximation of the input image.

A system comprises an encoder configured to compress and encode data for a three-dimensional dynamic mesh. The three-dimensional dynamic mesh is compressed and signaled using a base-mesh sub-bitstream and an atlas sub-bitstream (e.g., displacement and / or attribute sub-bitstream). The atlas sub-bitstream comprises displacement information to be applied at sub-division points of the base mesh to recreate the three-dimensional dynamic mesh at a given moment in time and may also include attribute values, such as colors, textures, etc. to be applied to the reconstructed mesh. Sub-mesh identifiers are included in tile headers of an atlas sub-bitstream that enable selective reconstruction of sub-meshes. A complimentary decoder decodes a compressed bitstream for the three-dimensional dynamic mesh, encoded such as by the encoder.

A method and apparatus for video coding are disclosed. According to the method for the decoder side, a first syntax, related to whether the current block is coded in a CCLM related mode, is parsed from a bitstream comprising the encoded data for the current block. If the first syntax indicates the current block being coded in the CCLM related mode, a second syntax is parsed from the bitstream, wherein the second syntax is related to whether a multiple model CCLM mode is used or whether one or more model parameters are explicitly signalled or implicitly derived. The model parameters for the second-colour block are determined if the first syntax indicates the current block being coded in a CCLM related mode. The encoded data associated with the second-colour block is then decoded using prediction data comprising the cross-colour predictor for the second-colour block.

There is provided an information processing device and method that can mitigate a reduction in the quality of 3D data due to encoding and decoding. A bitstream is decoded, the bitstream having been obtained by dividing a mesh that represents an object with a three-dimensional structure into at least a first patch and a second patch, placing the first patch and the second patch within a single image, and encoding the single image. A boundary correction process is executed to correct a geometry for a boundary vertex located at a boundary of the patches decoded. The boundary vertex subjected to the boundary correction process is set as a reference point, and a smoothing process is executed to smooth a geometry for a vertex within a partial area based on the reference point. The present disclosure may be applied to, for example, an information processing device, an electronic device, an information processing method, a program, or the like.

Various embodiments provide example apparatus, method, and computer program product. An example apparatus includes: receiving or generating a first encoded bitstream comprising independently encoded subpictures; receiving or generating a second encoded bitstream comprising independently encoded subpictures; wherein resolution of subpictures in the second encoded bitstream is same or substantially same as resolution of corresponding subpictures in the first encoded bitstream; generating an encapsulated file with a first track and second track, the first track comprises the first encoded bitstream comprising the independently encoded subpicture, the second track comprises the second encoded bitstream comprising the independently encoded subpictures; and wherein generating the encapsulated file comprises including following information in the encapsulated file: a picture-in-picture relationship between the first track and second track; and data units independently encoded subpictures in the first encoded bitstream that are to be replaced by data units of the independently encoded subpictures of the second encoded bitstream.

Embodiments of the present disclosure provide a solution for video processing. A method for video processing is proposed. The method comprises: determining, for a conversion between a current video block of a video and a bitstream of the video, a sign prediction of a block vector difference (BVD) of the current video block; determining the BVD at least based on the sign prediction of the BVD; and performing the conversion based on the BVD.

Embodiments of the present disclosure provide a solution for video processing. A method for video processing is proposed. The method comprises: determining, for a conversion between a current video block of a video and a bitstream of the video, at least one history-based motion vector prediction (HMVP) table of the current video block based on at least one of the following: a motion vector (MV) difference threshold for comparing at least two MVs of at least two HMVP candidates, a coding mode of the current video block, or a reference picture list index associated with the current video block; and performing the conversion based on the at least one HMVP table.