Granted Patent B2

US 12,225,205 · App. 17/825,575 · Granted Feb 11, 2025

Inventors: Sheng Lin (San Jose, CA); Wei Jiang (Sunnyvale, CA); Shan Liu (San Jose, CA); Wei Wang (Palo Alto, CA)

Assignee: TENCENT AMERICA LLC

H04N19/149H04N19/176H04N19/60H04N19/91

Abstract

Claims (35)

1. A method performed by at least one processor in a video encoder, the method comprising:

receiving a bitstream that includes an image;

partitioning the image into a plurality of blocks;

compressing each of the plurality of blocks by a neural network-based encoder;

obtaining compressed features by obtaining a compressed feature for each block from among the plurality of blocks in the image;

processing the compressed features by an entropy encoder to generate a first compressed bitstream;

obtaining a plurality of reshaped compressed features by concatenating the compressed features such that a number of reshaped compressed features is less than a number of compressed features, wherein the concatenating the compressed features comprises concatenating the compressed feature blocks into reshaped compressed feature blocks that are larger than the compressed feature blocks, wherein a first reshaped compressed feature block has a square shape and a second reshaped feature block has a rectangular shape, wherein at least two of the reshaped compressed feature blocks are a different size from each other;

processing the plurality of reshaped compressed features by the entropy encoder to generate a second compressed bitstream; and

encoding the bitstream including the image based on the second compressed bitstream.

2. The method according to claim 1 , wherein

the obtaining the compressed features comprises obtaining compressed feature blocks; and.

3. The method according to claim 1 , wherein the encoding the bitstream comprises including an indicator in the encoded bitstream that indicates that the compressed features were concatenated.

4. The method according to claim 1 , further comprises sending the encoded bitstream to a decoder.

5. A system comprising:

at least one memory configured to store computer program code; and

at least one processor configured to access the computer program code and operate as instructed by the computer program code, the computer program code comprising encoding code that is configured to cause the at least one processor to:

partition an image, from a bitstream, into a plurality of blocks;

compress each of the plurality of blocks by a neural network-based encoder;

obtain compressed features by obtaining a compressed feature for each block from among the plurality of blocks in the image;

process the compressed features by an entropy encoder to generate a first compressed bitstream;

obtain a plurality of reshaped compressed features by concatenating the compressed features such that a number of reshaped compressed features is less than a number of compressed features, wherein the concatenating the compressed features comprises concatenating the compressed feature blocks into reshaped compressed feature blocks that are larger than the compressed feature blocks, wherein a first reshaped compressed feature block has a square shape and a second reshaped feature block has a rectangular shape, wherein at least two of the reshaped compressed feature blocks are a different size from each other;

process the plurality of reshaped compressed features by the entropy encoder to generate a second compressed bitstream; and

encode the bitstream including the image based on the second compressed bitstream.

6. The system according to claim 5 , wherein

the compressed features are compressed feature blocks.

7. The system according to claim 5 , wherein the encoding code is configured to cause the at least one processor to include an indicator in the encoded bitstream that indicates that the compressed features were concatenated.

8. A non-transitory computer-readable medium storing computer code that is configured to, when executed by at least one processor, cause the at least one processor to implement a video encoder that:

receives a bitstream that includes an image;

partitions the image into a plurality of blocks;

compresses each of the plurality of blocks by a neural network-based encoder;

obtains compressed features by obtaining a compressed feature for each block from among the plurality of blocks in the image;

processes the compressed features by an entropy encoder to generate a first compressed bitstream;

obtains a plurality of reshaped compressed features by concatenating the compressed features such that a number of reshaped compressed features is less than a number of compressed features, wherein the concatenating the compressed features comprises concatenating the compressed feature blocks into reshaped compressed feature blocks that are larger than the compressed feature blocks, wherein a first reshaped compressed feature block has a square shape and a second reshaped feature block has a rectangular shape, wherein at least two of the reshaped compressed feature blocks are a different size from each other;

processes the plurality of reshaped compressed features by the entropy encoder to generate a second compressed bitstream; and

encodes the bitstream including the image based on the second compressed bitstream.

Assignments (1)

Continuity (2)

References Cited (46)