-
公开(公告)号：US11900525B2
公开(公告)日：2024-02-13
申请号：US17708628
申请日：2022-03-30
Applicant: Google LLC
Inventor： Philip Andrew Chou , Berivan Isik , Sung Jin Hwang , Nicholas Milo Johnston , George Dan Toderici
IPC: G06T15/08 , H04N19/176 , H04N19/46
CPC classification number: G06T15/08 , H04N19/176 , H04N19/46
Abstract: Example embodiments of the present disclosure relate to systems and methods for compressing attributes of volumetric and hypervolumetric datasets. An example system performs operations including obtaining a reference dataset comprising attributes indexed by a domain of multidimensional coordinates; subdividing the domain into a plurality of blocks respectively associated with a plurality of attribute subsets; inputting, to a local nonlinear operator, a latent representation for an attribute subset associated with at least one block of the plurality of blocks; obtaining, using the local nonlinear operator and based on the latent representation, an attribute representation of one or more attributes of the attribute subset; and updating the latent representation based on a comparison of the attribute representation and the reference dataset.
-
公开(公告)号：US11670010B2
公开(公告)日：2023-06-06
申请号：US17578794
申请日：2022-01-19
Applicant: Google LLC
Inventor： David Charles Minnen , Saurabh Singh , Johannes Balle , Troy Chinen , Sung Jin Hwang , Nicholas Johnston , George Dan Toderici
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.
-
公开(公告)号：US11257254B2
公开(公告)日：2022-02-22
申请号：US16515586
申请日：2019-07-18
Applicant: Google LLC
Inventor： David Charles Minnen , Saurabh Singh , Johannes Balle , Troy Chinen , Sung Jin Hwang , Nicholas Johnston , George Dan Toderici
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.
-
公开(公告)号：US20240195985A1
公开(公告)日：2024-06-13
申请号：US18286574
申请日：2021-05-07
Applicant: Google LLC
IPC: H04N19/176 , H04N19/119 , H04N19/159
CPC classification number: H04N19/176 , H04N19/119 , H04N19/159
Abstract: Methods, systems, and apparatus, including computer programs, for compression and decompression of video data using an ensemble of machine learning models. Methods can include defining for each frame in a video, a plurality of blocks in the frame. Methods can further include processing the frames of video in sequential sets, wherein each sequential set is at least a current frame (220) of video and a prior frame (240) of video in the ordered sequence. Each respective prediction of a block in the frame of the video includes providing, as input to a prediction model a first and the second border (235,230) of a current block (225) of the current frame, a first and a second border (250, 255) for a respective current block (245) of the prior frame and the respective current block (245) of the prior frame.
-
公开(公告)号：US11250595B2
公开(公告)日：2022-02-15
申请号：US16617484
申请日：2018-05-29
Applicant: GOOGLE LLC
Inventor： Michele Covell , Damien Vincent , David Charles Minnen , Saurabh Singh , Sung Jin Hwang , Nicholas Johnston , Joel Eric Shor , George Dan Toderici
Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for image compression and reconstruction. An image encoder system receives a request to generate an encoded representation of an input image that has been partitioned into a plurality of tiles and generates the encoded representation of the input image. To generate the encoded representation, the system processes a context for each tile using a spatial context prediction neural network that has been trained to process context for an input tile and generate an output tile that is a prediction of the input tile. The system determines a residual image between the particular tile and the output tile generated by the spatial context prediction neural network by process the context for the particular tile and generates a set of binary codes for the particular tile by encoding the residual image using an encoder neural network.
-
Patent Agency Ranking
公开(公告)号：US11177823B2
公开(公告)日：2021-11-16
申请号：US15985340
申请日：2018-05-21
Applicant: Google LLC
Inventor： David Charles Minnen , Michele Covell , Saurabh Singh , Sung Jin Hwang , George Dan Toderici
Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for compressing and decompressing data. In one aspect, an encoder neural network processes data to generate an output including a representation of the data as an ordered collection of code symbols. The ordered collection of code symbols is entropy encoded using one or more code symbol probability distributions. A compressed representation of the data is determined based on the entropy encoded representation of the collection of code symbols and data indicating the code symbol probability distributions used to entropy encode the collection of code symbols. In another aspect, a compressed representation of the data is decoded to determine the collection of code symbols representing the data. A reconstruction of the data is determined by processing the collection of code symbols by a decoder neural network.
-
公开(公告)号：US20240144583A1
公开(公告)日：2024-05-02
申请号：US18398009
申请日：2023-12-27
Applicant: Google LLC
Inventor： Philip Andrew Chou , Berivan Isik , Sung Jin Hwang , Nicholas Milo Johnston , George Dan Toderici
IPC: G06T15/08 , H04N19/176 , H04N19/46
CPC classification number: G06T15/08 , H04N19/176 , H04N19/46
Abstract: Example embodiments of the present disclosure relate to systems and methods for compressing attributes of volumetric and hypervolumetric datasets. An example system performs operations including obtaining a reference dataset comprising attributes indexed by a domain of multidimensional coordinates; subdividing the domain into a plurality of blocks respectively associated with a plurality of attribute subsets; inputting, to a local nonlinear operator, a latent representation for an attribute subset associated with at least one block of the plurality of blocks; obtaining, using the local nonlinear operator and based on the latent representation, an attribute representation of one or more attributes of the attribute subset; and updating the latent representation based on a comparison of the attribute representation and the reference dataset.
-
公开(公告)号：US20240078712A1
公开(公告)日：2024-03-07
申请号：US18306771
申请日：2023-04-25
Applicant: Google LLC
Inventor： David Charles Minnen , Saurabh Singh , Johannes Balle , Troy Chinen , Sung Jin Hwang , Nicholas Johnston , George Dan Toderici
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.
-
公开(公告)号：US20200027247A1
公开(公告)日：2020-01-23
申请号：US16515586
申请日：2019-07-18
Applicant: Google LLC
Inventor： David Charles Minnen , Saurabh Singh , Johannes Balle , Troy Chinen , Sung Jin Hwang , Nicholas Johnston , George Dan Toderici
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.
-
公开(公告)号：US20190356330A1
公开(公告)日：2019-11-21
申请号：US15985340
申请日：2018-05-21
Applicant: Google LLC
Inventor： David Charles Minnen , Michele Covell , Saurabh Singh , Sung Jin Hwang , George Dan Toderici
Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for compressing and decompressing data. In one aspect, an encoder neural network processes data to generate an output including a representation of the data as an ordered collection of code symbols. The ordered collection of code symbols is entropy encoded using one or more code symbol probability distributions. A compressed representation of the data is determined based on the entropy encoded representation of the collection of code symbols and data indicating the code symbol probability distributions used to entropy encode the collection of code symbols. In another aspect, a compressed representation of the data is decoded to determine the collection of code symbols representing the data. A reconstruction of the data is determined by processing the collection of code symbols by a decoder neural network.
-
-
-
-
-
-
-
-
-
Search Results
16
records
(took 0.015 seconds)
