Patent classifications
H04N19/42
Vector Quantization for Prediction Residual Coding
Residual coding using vector quantization (VQ) is described. A flag indicating whether a residual block for the current block is encoded using VQ. In response to the flag indicating that the residual block is encoded using VQ, a parameter indicating an entry in a codebook is decoded, and the residual block is decoded using the entry. In response to the flag indicating that the residual block is not encoded using VQ, the residual block is decoded based on a skip flag indicating whether the current block is encoded using transform skip. The current block is reconstructed using the residual block.
Vector Quantization for Prediction Residual Coding
Residual coding using vector quantization (VQ) is described. A flag indicating whether a residual block for the current block is encoded using VQ. In response to the flag indicating that the residual block is encoded using VQ, a parameter indicating an entry in a codebook is decoded, and the residual block is decoded using the entry. In response to the flag indicating that the residual block is not encoded using VQ, the residual block is decoded based on a skip flag indicating whether the current block is encoded using transform skip. The current block is reconstructed using the residual block.
INHERITANCE IN SAMPLE ARRAY MULTITREE SUBDIVISION
A better compromise between encoding complexity and achievable rate distortion ratio, and/or to achieve a better rate distortion ratio is achieved by using multitree sub-divisioning not only in order to subdivide a continuous area, namely the sample array, into leaf regions, but using the intermediate regions also to share coding parameters among the corresponding collocated leaf blocks. By this measure, coding procedures performed in tiles—leaf regions—locally, may be associated with coding parameters individually without having to, however, explicitly transmit the whole coding parameters for each leaf region separately. Rather, similarities may effectively exploited by using the multitree subdivision.
Multimedia Redirection Method, Device, and System
A multimedia redirection method comprising receiving, by a server, a hardware decoding capability sent by a client, where the hardware decoding capability is a hardware decoding capability that is in a video hardware acceleration specification and that is converted from a hardware decoding capability of a non-Windows operating system by the client; restoring, by the server, video data to a video code stream of a standard encoding format after receiving the hardware decoding capability; and sending, by the server, the video code stream to the client for decoding and display.
Multimedia Redirection Method, Device, and System
A multimedia redirection method comprising receiving, by a server, a hardware decoding capability sent by a client, where the hardware decoding capability is a hardware decoding capability that is in a video hardware acceleration specification and that is converted from a hardware decoding capability of a non-Windows operating system by the client; restoring, by the server, video data to a video code stream of a standard encoding format after receiving the hardware decoding capability; and sending, by the server, the video code stream to the client for decoding and display.
SIGNALING COLOR VALUES FOR 3D LOOKUP TABLE FOR COLOR GAMUT SCALABILITY IN MULTI-LAYER VIDEO CODING
Techniques are described for signaling information used to generate three-dimensional (3D) color lookup tables for color gamut scalability in multi-layer video coding. A lower layer of video data may include color data in a first color gamut and a higher layer of the video data may include color data in a second color gamut. To generate inter-layer reference pictures, a video encoder and/or video decoder performs color prediction to convert the color data of a reference picture in the first color gamut to the second color gamut. The video coder may perform color prediction using a 3D lookup table. According to the techniques, a video encoder may encode partition information and/or color values of a 3D lookup table generated for color gamut scalability. A video decoder may decode the partition information and/or color values to generate the 3D lookup table in order to perform color gamut scalability.
SIGNALING COLOR VALUES FOR 3D LOOKUP TABLE FOR COLOR GAMUT SCALABILITY IN MULTI-LAYER VIDEO CODING
Techniques are described for signaling information used to generate three-dimensional (3D) color lookup tables for color gamut scalability in multi-layer video coding. A lower layer of video data may include color data in a first color gamut and a higher layer of the video data may include color data in a second color gamut. To generate inter-layer reference pictures, a video encoder and/or video decoder performs color prediction to convert the color data of a reference picture in the first color gamut to the second color gamut. The video coder may perform color prediction using a 3D lookup table. According to the techniques, a video encoder may encode partition information and/or color values of a 3D lookup table generated for color gamut scalability. A video decoder may decode the partition information and/or color values to generate the 3D lookup table in order to perform color gamut scalability.
MULTI-DOMAIN CONVOLUTIONAL NEURAL NETWORK
In one embodiment, an apparatus comprises a memory and a processor. The memory is to store visual data associated with a visual representation captured by one or more sensors. The processor is to: obtain the visual data associated with the visual representation captured by the one or more sensors, wherein the visual data comprises uncompressed visual data or compressed visual data; process the visual data using a convolutional neural network (CNN), wherein the CNN comprises a plurality of layers, wherein the plurality of layers comprises a plurality of filters, and wherein the plurality of filters comprises one or more pixel-domain filters to perform processing associated with uncompressed data and one or more compressed-domain filters to perform processing associated with compressed data; and classify the visual data based on an output of the CNN.
Intra Prediction Method and Apparatus
An intra prediction method includes obtaining respective intra prediction modes or texture distributions of P reconstructed picture blocks in a surrounding region of a current block; obtaining, based on the respective intra prediction modes or texture distributions of the P reconstructed picture blocks, Q priori candidate intra prediction modes of the current block and Q probability values; obtaining, based on M probability values corresponding to M priori candidate intra prediction modes, M weighting factors corresponding to the M priori candidate intra prediction modes; separately performing intra prediction based on the M priori candidate intra prediction modes to obtain M predicted values; and obtaining a predicted value of the current block based on a weighted summation of the M predicted values and the corresponding M weighting factors.
Intra Prediction Method and Apparatus
An intra prediction method includes obtaining respective intra prediction modes or texture distributions of P reconstructed picture blocks in a surrounding region of a current block; obtaining, based on the respective intra prediction modes or texture distributions of the P reconstructed picture blocks, Q priori candidate intra prediction modes of the current block and Q probability values; obtaining, based on M probability values corresponding to M priori candidate intra prediction modes, M weighting factors corresponding to the M priori candidate intra prediction modes; separately performing intra prediction based on the M priori candidate intra prediction modes to obtain M predicted values; and obtaining a predicted value of the current block based on a weighted summation of the M predicted values and the corresponding M weighting factors.