Invention Grant
- Patent Title: Data compression using conditional entropy models
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Application No.: US17578794Application Date: 2022-01-19
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Publication No.: US11670010B2Publication Date: 2023-06-06
- Inventor: David Charles Minnen , Saurabh Singh , Johannes Balle , Troy Chinen , Sung Jin Hwang , Nicholas Johnston , George Dan Toderici
- Applicant: Google LLC
- Applicant Address: US CA Mountain View
- Assignee: Google LLC
- Current Assignee: Google LLC
- Current Assignee Address: US CA Mountain View
- Agency: Fish & Richardson P.C.
- Main IPC: G06T9/00
- IPC: G06T9/00 ; G06N20/00 ; G06F17/18 ; G06N3/08 ; G06T3/40

Abstract:
Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for compressing and decompressing data. In one aspect, a method comprises: processing data using an encoder neural network to generate a latent representation of the data; processing the latent representation of the data using a hyper-encoder neural network to generate a latent representation of an entropy model; generating an entropy encoded representation of the latent representation of the entropy model; generating an entropy encoded representation of the latent representation of the data using the latent representation of the entropy model; and determining a compressed representation of the data from the entropy encoded representations of: (i) the latent representation of the data and (ii) the latent representation of the entropy model used to entropy encode the latent representation of the data.
Public/Granted literature
- US20220138991A1 DATA COMPRESSION USING CONDITIONAL ENTROPY MODELS Public/Granted day:2022-05-05
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