Attention Based Context Modelling for Image and Video Compression
AssigneeHuawei Technologies Co., Ltd.
InventorsAhmet Burakhan Koyuncu, Han Gao, Atanas Boev, Elena Alexandrovna Alshina
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Abstract
Methods and apparatuses are described for entropy encoding and decoding of a latent tensor, which includes separating the latent tensor into segments in the spatial dimensions, each segment including at least one latent tensor element. An arrangement of the segments is processed by a neural network; the neural network includes at least one attention layer. Based on the processed segment a probability model is obtained for entropy encoding or decoding of a latent tensor element.
Claims25
A method for entropy encoding of a latent tensor, comprising:
- separating the latent tensor into a plurality of segments in spatial dimensions, each segment of the plurality of segments including at least one latent tensor element;
- processing an arrangement of the plurality of segments by one or more layers of a neural network, the neural network including at least one attention layer;
- and
- obtaining a probability model for the entropy encoding of a current element of the latent tensor based on the processed plurality of segments.
A method for entropy decoding of a latent tensor, comprising:
- initializing the latent tensor with zeroes;
- separating the latent tensor into a plurality of segments in spatial dimensions, each segment of the plurality of segments including at least one latent tensor element;
- processing an arrangement of the plurality of segments by one or more layers of a neural network, the neural network including at least one attention layer;
- and
- obtaining a probability model for the entropy decoding of a current element of the latent tensor based on the processed plurality of segments.
An apparatus for entropy encoding of a latent tensor, comprising:
- processing circuitry configured to:
- separate the latent tensor into a plurality of segments in spatial dimensions, each segment of the plurality of segments including at least one latent tensor element;
- process an arrangement of the plurality of segments by one or more layers of a neural network, the neural network including at least one attention layer;
- and
- obtain a probability model for the entropy encoding of a current element of the latent tensor based on the processed plurality of segments.
An apparatus for entropy decoding of a latent tensor, comprising:
- processing circuitry configured to:
- initialize the latent tensor with zeroes;
- separate the latent tensor into a plurality of segments in spatial dimensions, each segment of the plurality of segments including at least one latent tensor element;
- process an arrangement of the plurality of segments by one or more layers of a neural network, the neural network including at least one attention layer;
- and
- obtain a probability model for the entropy decoding of a current element of the latent tensor based on the processed plurality of segments.
Dependencies are inferred from the claim text.