Patent ID: 11915457
Assignee: TENCENT AMERICA LLC
Field: Audio-visual technology (Electrical engineering)
Classification: CPC G  H | IPC G

Claim 0:
1. A method of adaptive neural image compression with rate control by meta-learning, the method being performed by at least one processor, and the method comprising:
receiving a recovered compressed representation and a hyperparameter of an image; and
decoding the received recovered compressed representation based on a received hyperparameter, using a decoded neural network, to reconstruct an output image, wherein the received recovered compressed representation is based on:
receiving an input image and the hyperparameter; and
encoding the received input image, based on the received hyperparameter, using an encoding neural network, to generate a compressed representation, wherein the encoding comprises:
performing a first shared encoding on the received input image, using a first shared encoding layer having first shared encoding parameters;
performing a first adaptive encoding on the received input image, using a first adaptive encoding layer having first adaptive encoding parameters;
combining the first shared encoded input image and the first adaptive encoded input image, to generate a first combined output; and
performing a second shared encoding on the first combined output, using a second shared encoding layer having second shared encoding parameters, and

wherein decoding the received recovered compressed representation comprises:
performing a first shared decoding on the received recovered compressed representation, using a first shared decoding layer having first shared decoding parameters;
performing a first adaptive decoding on the received recovered compressed representation, using a first adaptive decoding layer having first adaptive decoding parameters; and
combining the first shared decoded recovered compressed representation and the first adaptive decoded recovered compressed representation, to generate a second combined output.