Abstract: An encoding method includes: first obtaining to-be-encoded data, and then inputting the to-be-encoded data into a first encoding network to obtain a target parameter; then constructing a second encoding network based on the target parameter; next inputting the to-be-encoded data into the second encoding network to obtain a first feature; and finally encoding the first feature to obtain an encoded bitstream.

Abstract: This application provides a scalable encoding and decoding method and apparatus. The encoding method includes: applying a control signal of a first signal component of a video signal to a first feature map of the first signal component, to obtain a second feature map of the first signal component, where the control signal of the first signal component is obtained through learning; applying a control signal of a second signal component of the video signal to a first feature map of the second signal component, to obtain a second feature map of the second signal component, where the control signal of the second signal component is obtained through learning; and obtaining a bitstream of the video signal based on the second feature map of the first signal component and the second feature map of the second signal component.

Abstract: This application provides a scalable encoding and decoding method and apparatus. The encoding method includes: applying a control signal of a first signal component of a video signal to a first feature map of the first signal component, to obtain a second feature map of the first signal component, where the control signal of the first signal component is obtained through learning; applying a control signal of a second signal component of the video signal to a first feature map of the second signal component, to obtain a second feature map of the second signal component, where the control signal of the second signal component is obtained through learning; and obtaining a bitstream of the video signal based on the second feature map of the first signal component and the second feature map of the second signal component.

Abstract: An image processing method and apparatus are provided. The method includes: obtaining an image; performing feature extraction on the image to obtain at least one first feature map, wherein the at least one first feature map includes N first feature values, and N is a positive integer; obtaining a target compression bit rate which corresponds to M target gain values, each target gain value corresponds to one first feature value, and M is a positive integer less than or equal to N; respectively processing corresponding first feature values based on the M target gain values to obtain M second feature values; and performing quantization and entropy encoding on at least one processed first feature map to obtain encoded data, wherein the at least one processed first feature map includes the M second feature values. According to the application, compression bit rate control is implemented in a same compression model.

Abstract: An image processing method and apparatus are provided. The method includes: obtaining an image; performing feature extraction on the image to obtain at least one first feature map, wherein the at least one first feature map includes N first feature values, and N is a positive integer; obtaining a target compression bit rate which corresponds to M target gain values, each target gain value corresponds to one first feature value, and M is a positive integer less than or equal to N; respectively processing corresponding first feature values based on the M target gain values to obtain M second feature values; and performing quantization and entropy encoding on at least one processed first feature map to obtain encoded data, wherein the at least one processed first feature map includes the M second feature values. According to the application, compression bit rate control is implemented in a same compression model.

Abstract: This application discloses encoding and decoding methods and apparatuses, and relates to the field of artificial intelligence technologies, to improve rate distortion performance of data encoding and decoding methods. The method includes: first obtaining to-be-encoded data, and then inputting the to-be-encoded data into a first encoding network to obtain a target parameter; then constructing a second encoding network based on the target parameter; next inputting the to-be-encoded data into the second encoding network to obtain a first feature; and finally encoding the first feature to obtain an encoded bitstream.

Abstract: This application provides a scalable encoding and decoding method and apparatus. The encoding method includes: applying a control signal of a first signal component of a video signal to a first feature map of the first signal component, to obtain a second feature map of the first signal component, where the control signal of the first signal component is obtained through learning; applying a control signal of a second signal component of the video signal to a first feature map of the second signal component, to obtain a second feature map of the second signal component, where the control signal of the second signal component is obtained through learning; and obtaining a bitstream of the video signal based on the second feature map of the first signal component and the second feature map of the second signal component.

Abstract: This application discloses an image processing method, including: obtaining an image; performing feature extraction on the image to obtain at least one first feature map, where the at least one first feature map includes N first feature values, and N is a positive integer; obtaining a target compression bit rate, where the target compression bit rate corresponds to M target gain values, each target gain value corresponds to one first feature value, and M is a positive integer less than or equal to N; respectively processing corresponding first feature values based on the M target gain values to obtain M second feature values; and performing quantization and entropy encoding on at least one processed first feature map to obtain encoded data, where the at least one processed first feature map includes the M second feature values. Thus, compression bit rate control can be implemented in a same compression model.