公开(公告)号：US20240323415A1

公开(公告)日：2024-09-26

申请号：US18188070

申请日：2023-03-22

Applicant: QUALCOMM Incorporated

Inventor： David Wilson ROMERO GUZMAN ,  Gabriele CESA ,  Guillaume Konrad SAUTIERE ,  Yunfan ZHANG ,  Taco Sebastiaan COHEN ,  Auke Joris WIGGERS

IPC: H04N19/42 ,  G06T3/40 ,  H04N19/182

CPC classification number: H04N19/42 ,  G06T3/4046 ,  H04N19/182

Abstract: Certain aspects of the present disclosure provide techniques and apparatus for encoding content using a neural network. An example method generally includes encoding video content into a latent space representation through an encoder implemented by a first machine learning model. A code is generated by upsampling the latent space representation of the video content. A prior is calculated based on a conditional probability of obtaining the upsampled latent space representation conditioned by the latent space representation of the video content. A compressed version of the video content is generated based on a probabilistic model implemented by a second machine learning model, the generated code, and the calculated prior, and the compressed version of the video content is output for transmission.

公开(公告)号：US20230074979A1

公开(公告)日：2023-03-09

申请号：US17411936

申请日：2021-08-25

Applicant: QUALCOMM Incorporated

Inventor： Johann Hinrich BREHMER ,  Ties Jehan VAN ROZENDAAL ,  Yunfan ZHANG ,  Taco Sebastiaan COHEN

IPC: G06N3/08 ,  G06K9/62

Abstract: Techniques are described for compressing data using machine learning systems. An example process can include receiving input data for compression by a neural network compression system. The process can include determining, based on the input data, a set of updated model parameters for the neural network compression system, wherein the set of updated model parameters is selected from a subspace of model parameters. The process can include generating at least one bitstream including a compressed version of the input data and a compressed version of one or more subspace coordinates that correspond to the set of updated model parameters. The process can include outputting the at least one bitstream for transmission to a receiver.

公开(公告)号：US20220385907A1

公开(公告)日：2022-12-01

申请号：US17645018

申请日：2021-12-17

Applicant: QUALCOMM Incorporated

Inventor： Yunfan ZHANG ,  Ties Jehan VAN ROZENDAAL ,  Taco Sebastiaan COHEN ,  Markus NAGEL ,  Johann Hinrich BREHMER

IPC: H04N19/126 ,  G06T9/00 ,  G06N3/08 ,  G06N3/04 ,  H04N19/147 ,  H04N19/91

Abstract: Techniques are described for compressing and decompressing data using machine learning systems. An example process can include receiving a plurality of images for compression by a neural network compression system. The process can include determining, based on a first image from the plurality of images, a first plurality of weight values associated with a first model of the neural network compression system. The process can include generating a first bitstream comprising a compressed version of the first plurality of weight values. The process can include outputting the first bitstream for transmission to a receiver.