Huawei Technologies Co., Limited

Jue Mao

Haitao Yang

Yin Zhao

Lu Yu

Xiang Ma

The technology of this application relates to an entropy encoding method that includes obtaining base layer information of a to-be-encoded picture block, where the base layer information corresponds to M samples in the picture block, and M is a positive integer, obtaining K elements corresponding to enhancement layer information of the picture block, where the enhancement layer information corresponds to N samples in the picture block, both K and N are positive integers, and N≥M, inputting the base layer information into a neural network to obtain K groups of probability values, where the K groups of probability values correspond to the K elements, and any group of probability values is for representing probabilities of a plurality of candidate values of a corresponding element, and performing entropy encoding on the K elements based on the K groups of probability values.

Entropy encoding/decoding method and apparatus

A motion vector prediction method and device, includes determining a motion vector type of the motion vector of the current block based on a reference frame type of the reference frame, obtaining a motion vector type of a first motion vector of at least one spatially adjacent prediction block of the current block when the at least one spatially adjacent prediction block is an inter-frame prediction block, and when the obtained motion vector type of the first motion vector is different from all motion vector types of motion vectors of the current block, determining a second motion vector of a spatially adjacent pixel block of the current block based on decoding information of the spatially adjacent pixel block, and using the second motion vector or a scaling value of the second motion vector as a candidate motion vector predictor of the current block.

Growing community of inventors

Hangzhou, China

Jue Mao