- Patent Title: Channel-wise autoregressive entropy models for image compression
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Application No.: US17021688Application Date: 2020-09-15
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Publication No.: US11538197B2Publication Date: 2022-12-27
- Inventor: David Charles Minnen , Saurabh Singh
- 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 ; G06F17/18 ; G06N3/04 ; G06N3/08

Abstract:
Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for channel-wise autoregressive entropy models. In one aspect, a method includes processing data using a first encoder neural network to generate a latent representation of the data. The latent representation of data is processed by a quantizer and a second encoder neural network to generate a quantized latent representation of data and a latent representation of an entropy model. The latent representation of data is further processed into a plurality of slices of quantized latent representations of data wherein the slices are arranged in an ordinal sequence. A hyperprior processing network generates a hyperprior parameters and a compressed representation of the hyperprior parameters. For each slice, a corresponding compressed representation is generated using a corresponding slice processing network wherein a combination of the compressed representations form a compressed representation of the data.
Public/Granted literature
- US20220084255A1 CHANNEL-WISE AUTOREGRESSIVE ENTROPY MODELS FOR IMAGE COMPRESSION Public/Granted day:2022-03-17
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