566 results about "Video decoder" patented technology

A video encoder and video decoder may determine to code a block of video data using a non-directional intra mode. The video encoder and video decoder may determine a secondary transform from a secondary transform set for the block, and perform a transform process on the block of video data using the secondary transform. For non-directional intra prediction modes, the secondary transform set has a first number of transform kernels that is less than a second number of transform kernels in the secondary transform set for other blocks coded using a directional intra mode.

The application provides a signal transmission method, a video encoder and a computer readable storage medium. A computer-implemented signal transmission method performed by an encoder comprises the following steps: a processor transmits a bitstream comprising weight information for a prediction coding unit (CU) to a video decoder, the weight information indicating that if weighted prediction is enabled for a bi-prediction mode of the CU, weighted averaging for the bi-prediction mode is disabled, and the weight information indicating that if weighted prediction is enabled for at least one of a luma component and a chroma component of a reference picture of the CU, weighted averaging for the bi-prediction mode is disabled, wherein the bitstream comprises a flag indicating whether weighted prediction is enabled for at least one of the luma component and the chroma component of the reference picture, and the flag comprises a flag luma_weight_lx_flag[i] transmitted for an i-th reference picture in a reference picture list Lx, wherein x is 0 or 1.

Systems, methods, and instrumentalities are disclosed herein for reducing the amortization gap in end-to-end image compression and / or video compression. In examples, a video decoder may obtain an entropy model indication in video data. Based on the entropy model indication, the decoder may determine an entropy model to use for decoding a current picture. The current picture may be decoded based on the determined entropy model. In examples, the entropy model indication may indicate whether to use an updated entropy model or a prior entropy model for decoding the current picture. In examples, the entropy model indication may indicate an updated entropy model or a learned entropy model to use for decoding the current picture.

A video decoder reconstructs a current frame of a video from a video bitstream based on a reconstructed reference frame. For a block of the current frame, the video decoder identifies a reference block in the reference frame based on a motion vector associated with the block. The decoder determines the slope and offset parameters of a local illumination compensation model based on reconstructed pixels in the current frame and the reference frame. The video decoder decodes, from the video bitstream, an adjustment to the slope and updates the slope by applying the decoded adjustment. The decoder further determines an adjusted offset parameter for the local illumination compensation model. The decoder generates predicted pixels for the block by at least applying, to the reference block, the local illumination compensation model with the updated parameters.

A video decoding method includes obtaining a to-be-entropy-decoded syntax element in a current block by parsing a received bitstream, where the to-be-entropy-decoded syntax element includes a syntax element 1 or a syntax element 2 in the current block, obtaining a context model corresponding to the to-be-entropy-decoded syntax element, where both of a context model corresponding to the syntax element 1 and a context model corresponding to the syntax element 2 are determined from the same preset context model set, entropy decoding the to-be-entropy-decoded syntax element based on the context model corresponding to the to-be-entropy-decoded syntax element, and obtaining a reconstructed image of the current block based on the syntax element obtained by entropy decoding.

Systems, methods, and instrumentalities are disclosed herein for the field of video coding. Examples herein may focus on the most probable mode (MPM) list. In examples, a video decoder device and / or a video encoder device may generate an MPM list for a current block. The encoder and / or decoder may reorder the MPM based on a reordering process for each mode of the MPM list. The decoder may perform prediction for the current block based on the reordered MPM list. The encoder may encoder the current block based on the reordered MPM list.

The invention relates to the technical field of video acquisition coding and transmission, and provides a WebRTC-based method for reducing transmission bandwidth and improving transmission stability, which comprises the following steps: S1, a video acquisition module acquires a video frame from a camera and sends the video frame to a video coding module; s2, performing AI scene detection on the video frame to obtain a picture scene of the video frame, and performing region-of-interest ROI detection on the video frame to obtain a region-of-interest ROI range of the video frame; s3, optimizing the original funnel algorithm, setting different code rates for different video frames according to different video frame scenes, and setting different code rates for different areas of the video frames according to different ROI (Region of Interest) ranges of the video frames; s4, encoding the video frame, and sending the encoded video frame to a receiving end; s5, the receiving end decodes the received compressed video data into original video frames by using a video decoder; and S6, transmitting the decoded video frame to a rendering module for video rendering and display. The transmission bandwidth is reduced, and the transmission stability is improved.

A video decoder can be configured to determine that a current block of the video data is coded in a bi-prediction inter mode; receive a first syntax element identifying a motion vector predictor from a first candidate list of motion vector predictors; receive a second syntax element identifying a motion vector difference; determine a first motion vector for the current block based on the motion vector predictor and the motion vector difference; determine a second motion vector for the current block from a second list of candidate motion vector predictors based on bilateral matching; and determine a prediction block for the current block using the first motion vector and the second motion vector.

A video dynamic mesh coding (v-DMC) decoding system, includes a de-multiplexer that receives and demultiplexes an encoded v-DMC bitstream into: a parameter set and mesh data, geometry, atlas data, and attribute video substreams. The decoding system also includes: a mesh data substream decoder; a video decoder that decodes the geometry data substream; an atlas data substream decoder; a mesh subdivision component that subdivides the one or more base meshes into one or more resampled base meshes based upon the decoded atlas data; a displacement decoder that outputs one or more displacements to verticies of the one or more resampled base meshes; a mesh position refinement component that applies the one or more displacements to the one or more resampled base meshes and outputs one or more resultant meshes; and a video decoder that decodes the attribute video substream into one or more texture images.

A method for in-loop sample offset filtering in a video decoder is disclosed. The method includes obtaining at least one statistical property associated with reconstructed samples of at least a first color component in a current reconstructed data block of a video stream, selecting a target sample offset filter among a plurality of sample offset filters based on the at least one statistical property, the target sample offset filter comprising a nonlinear mapping between sample delta measures and sample offset values, and filtering a current sample in a second color component of the current reconstructed data block using the target sample offset filter and reference samples in a third color component of the current reconstructed data block to generate a filtered reconstructed sample of the current sample.

The invention discloses a DVFS method of a hardware video decoder. The DVFS method comprises the following steps. And S31, counting the number of to-be-decoded code stream caches and the number of to-be-filled video frame caches in the video decoding system, calling a'to-be-decoded code stream cache 'and a'to-be-filled video frame cache' as a'to-be-decoded cache pair ', and representing the workload of a hardware video decoder at a moment by using the number of the'to-be-decoded cache pair' at the moment. And S32, according to the real-time working load of the hardware video decoder, determining the relative relationship between the decoding performance and the decoding demand of the hardware video decoder at the moment, and calculating the new working frequency of the hardware video decoder according to the relative relationship. And step S33, adjusting the working frequency of the hardware video decoder to a new working frequency. The method has the advantages of being small in calculation amount, good in adaptability and high in real-time performance.

A video encoder and video decoder may include a video syntax processing (VSP) engine configured to process the video data at a syntax element level, and a video pixel processing (VPP) engine configured to process the video data at a pixel level. The video encoder and video decoder may further include a controller configured to control a power of the VSP engine based on the VSP engine being idle.

A video encoder is configured to determine to filter video data using a neural network (NN)-based filter and a fixed block size inference, and encode a flag that indicates the fixed block size inference is used for the NN-based filter. Reciprocally, a video decoder is configured to decode a flag that indicates whether a fixed block size inference is used for an NN-based filter, and filter video data using the NN-based filter based on the flag. The flag may be signaled at a sequence parameter set (SPS) level.

A method performed by at least one processor of a video decoder includes receiving a coded video bitstream including at least one picture and one or more syntax elements encoded in accordance with multi-hypothesis arithmetic coding. The method further includes decoding each syntax element from the one or more syntax elements based on the multi-hypothesis arithmetic coding. The method further includes selecting a probability update rate from a plurality of probability update rates based on a predetermined condition, the plurality of probability update rates including a first probability update rate that is higher than a second probability update rate. The method further includes updating at least one probability model utilized in the multi-hypothesis arithmetic coding based on the selected probability update rate. The method further includes decoding at least one block in the at least one picture based on the decoded one or more syntax elements.

A system configured to improve audio processing by performing audio-visual target speech enhancement. The system may include a deep neural network (DNN) configured to jointly mitigate additive noise, reverberation, and / or residual echo. The DNN may include an audio encoder / decoder network, which may correspond to a convolutional recurrent network configured to process complex-valued spectrograms corresponding to the isolated audio data generated during echo cancellation. In addition, the DNN may also include a video encoder / decoder network configured to process image data, enabling the DNN to make use of audio and visual modalities to enhance a target speech signal. Thus, the DNN may include (i) audio / video encoders that generate audio / image features, (ii) a fusion network that combines the audio / image features, and (iii) audio / video decoders that generate output data. By processing these multimodal inputs, the DNN may distinguish between desired speech associated with a face represented in the image data and interfering speech.

An example apparatus for decoding media data includes: a memory configured to store video data; and a processing system comprising one or more processors implemented in a circuit, the processing system configured to instantiate a first number of video decoder instances to be executed by the processing system; determining an attribute of the plurality of video media streams, the attribute indicating that each of the plurality of video media streams is available for stream selection; selecting the second number of input video media streams from the plurality of video media streams according to the determined attributes of the second number of input video media streams; executing the video decoder instance to decode the second number of input video media streams to form a second number of decoded video media streams; and outputting data of the second number of decoded video media streams.

Described embodiments provide systems and methods for latency optimization for cloud applications. An agent of a client device comprising an audio decoder and a video decoder can monitor video and audio data paths of an application communicating audio / video (A / V) data from one or more servers to the client device. The agent can measure, using the audio decoder and the video decoder, an A / V latency and a lip-sync status of the video and audio data paths of the application. The agent can determine, based on at least one or more measurements of the A / V latency and the lip-sync status, to enable a low latency mode for at least one of the video decoder or the audio decoder. The agent can configure, responsive to the determination, the low latency mode on one of the video decoder or the audio decoder.

A video encoder and video decoder are configured to perform neural network (NN)-based filtering. The video encoder and video decoder may receive a picture of video data, reconstruct the picture of video data, and perform an NN-based filter process on one or more blocks of the reconstructed picture of video data using an NN-based filter, wherein the NN-based filter includes a pair of backbone blocks, each of the pair of backbone blocks comprising a three-component one-dimensional (1D) decomposition of a multi-dimensional convolution, wherein the 1D decomposition includes at least one layer with feature channel reduction.

A video decoder is configured to determine, from the encoded video data, a block of a picture; apply a neural network (NN)-based filter to the block to generate a filtered block, wherein applying the NN-based filter comprises transforming the block of the picture with a transform block, wherein transforming the block of the picture with the transform block comprises rounding a floating point value to a nearest integer; determine a decoded version of the block based on the filtered block; and output a decoded version of the picture comprising the decoded version of the block.

A device for decoding video data includes an integrated circuit (IC) comprising a video decoder, and a memory that is external to the IC and coupled to the IC. The video decoder is configured to in a first mode, decode a first frame based on a first reference frame stored in the memory, and in a second mode, decode a second frame based on a second lossy reference frame, wherein the second lossy reference frame is generated based on decompression of a lossy compressed reference frame.

A video encoder and video decoder are configured to determine a filter from a first temporal layer having a first temporal layer ID, determine a scaling factor for the filter from a second temporal layer having a second temporal layer ID, and store the scaling factor in a buffer for future usage based on the second temporal layer ID being less than or equal to the first temporal layer ID.

A video decoder may be configured to identify chroma blocks in received video data. The video decoder may determine from the received video data that DM intra prediction applies to the chroma blocks. The video decoder may retrieve data associated with luma blocks that correspond to the identified chroma blocks. The data associated with the luma blocks may indicate that DIMD, TIMD, IntraTMP, and / or SGMP are associated with the luma blocks. The video decoder, on condition that the received data indicates DM intra prediction applies to the chroma blocks and the data associated with the corresponding luma blocks indicate DIMD, and / or TIMD, IntraTMP, and / or SGMP are to be applied to the luma blocks, may determine that DIMD, and / or TIMD, IntraTMP, and / or SGMP may similarly be applied to the corresponding chroma blocks.

The present disclosure discloses a video decoding method and a video decoder. The method includes: parsing coding tree split information to obtain a current node; determining coordinates of an upper-left corner of a region covered by a current quantization group based on a depth N of the current node; obtaining a QP delta of a current CU in the region covered by the current quantization group; and obtaining a reconstructed picture of the current CU based on the QP delta of the current CU.

To provide a video decoder, a video encoder, a method for decoding video content, a method for encoding video content, a computer program, and a video bitstream for implementing arithmetic encoding and decoding with optimal coding efficiency.SOLUTION: A video decoder comprises an arithmetic decoder for providing a decoded binary sequence on the basis of an encoded representation of a binary sequence. The arithmetic decoder is configured to determine a first source statistic value using a first estimation parameter and to determine a second source statistic value using a second estimation parameter. The arithmetic decoder is configured to determine a combined source statistic value on the basis of the first source statistic value (at) and on the basis of the second source statistic value. The arithmetic decoder is configured to determine one or more range values for an interval subdivision, which is used for mapping the encoded representation of the binary sequence onto the decoded binary sequence, on the basis of the combined source statistic value.SELECTED DRAWING: Figure 1

A video decoder is configured to determine, from encoded video data, a block of a picture; apply a neural network (NN)-based filter to the block to generate a filtered block, wherein to apply the NN-based filter, the one or processors process the block by a backbone block, wherein to process the block by the backbone block, the one or more processors are configured to: process input data for the block by a first activation layer; process an output of the first activation layer by a first convolution layer; process an output of the first convolution layer by a second activation layer; process an output of the second activation layer by a second convolution layer; and determine the filtered block based on an output of the second convolution layer.

Embodiments provide an arithmetic encoder for encoding a plurality of symbols having symbol values, wherein the arithmetic encoder is configured to determine one or more state variable values, which represent statistics of a plurality of previously encoded symbol values, and wherein the arithmetic encoder is configured to derive an interval size information for an arithmetic encoding of one or more symbol values to be encoded on the basis of one or more state variable values which represent statistics of a plurality of previously encoded symbol values. Furthermore, the arithmetic encoder is configured to selectively increase an adaptation speed of one or more of the state variable values for a predetermined number of bins following an initialization of the one or more state variable values; and / or to selectively reduce an adaptation speed of one or more of the state variable values when a predetermined number of bins following an initialization of one or more state variable values has passed; and / or to use a first, comparatively higher adaptation speed for adapting one or more of the state variable values to a probability of encoded symbol values for a first group of bins following an initialization of the one or more state variable values, and to use a second, comparatively lower adaptation speed for adapting one or more of the state variable values to a probability of encoded symbol values for a second group of bins following the first group of bins. Further arithmetic encoders, arithmetic decoders, video encoders, video decoder, methods for encoding, methods for decoding and computer programs are also disclosed which are based on the same concept and on other concepts.

A video decoder may be configured to determine that a block of video data is encoded using an intra prediction process that utilizes multiple intra prediction predictors; determine a set of reference lines for the intra prediction process; determine a first set of intra prediction predictors based on the set of reference lines; determine a second set of intra prediction predictors based on the set of reference lines; generate a fusion of predictors from the first set of intra prediction predictors and the second set of intra prediction predictors; and decode the block of video data using the fusion of predictors.

Intra prediction modes are determined for entry in most probable mode lists for encoding in video encoders and decoding in video decoders. In at least one embodiment, coding modes are derived to determine reference samples to use from inter coded neighboring blocks. In one embodiment, up to five neighboring blocks are used. The reference samples are used in an intra prediction mode to determined prediction samples. The reference samples are used for prediction in encoding or decoding. In at least one embodiment, one of several motion models can be used to extract the intra motion mode. The intra motion modes are used to fill a most probable mode list. The motion model, intra mode, or reference frame can be signaled from an encoder to a decoder.

A video frame codec architecture is disclosed. Techniques and apparatus for a video frame codec architecture are described. A frame decompressor decompresses compressed frames to produce decompressed frames. A frame decompressor controller arbitrates shared access to the frame decompressor. Multiple cores of a SoC request to receive decompressed frames from the frame decompressor via the frame decompressor controller. The frame decompressor controller can implement a request queue and can order the servicing of requests based on the priority of the request or the requesting core. The frame decompressor controller can also establish a time-sharing protocol for access by multiple cores. In some embodiments, a video decoder is integrated with the frame decompressor logic and stores portions of the decompressed frame in a video buffer, and a display controller retrieves the portion for display using a synchronization mechanism. In a similar manner, the frame compressor controller can arbitrate shared access to the frame compressor for multiple cores.