Patents by Inventor Joel Eric Shor

Joel Eric Shor has filed for patents to protect the following inventions. This listing includes patent applications that are pending as well as patents that have already been granted by the United States Patent and Trademark Office (USPTO).

  • Patent number: 11354822
    Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for image compression and reconstruction. A request to generate an encoded representation of an input image is received. The encoded representation of the input image is then generated. The encoded representation includes a respective set of binary codes at each iteration. Generating the set of binary codes for the iteration from an initial set of binary includes: for any tiles that have already been masked off during any previous iteration, masking off the tile. For any tiles that have not yet been masked off during any of the previous iterations, a determination is made as to whether a reconstruction error of the tile when reconstructed from binary codes at the previous iterations satisfies an error threshold. When the reconstruction quality satisfies the error threshold, the tile is masked off.
    Type: Grant
    Filed: May 16, 2018
    Date of Patent: June 7, 2022
    Assignee: Google LLC
    Inventors: Michele Covell, Damien Vincent, David Charles Minnen, Saurabh Singh, Sung Jin Hwang, Nicholas Johnston, Joel Eric Shor, George Dan Toderici
  • Patent number: 11250595
    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.
    Type: Grant
    Filed: May 29, 2018
    Date of Patent: February 15, 2022
    Assignee: Google LLC
    Inventors: Michele Covell, Damien Vincent, David Charles Minnen, Saurabh Singh, Sung Jin Hwang, Nicholas Johnston, Joel Eric Shor, George Dan Toderici
  • Publication number: 20210335017
    Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for image compression and reconstruction. A request to generate an encoded representation of an input image is received. The encoded representation of the input image is then generated. The encoded representation includes a respective set of binary codes at each iteration. Generating the set of binary codes for the iteration from an initial set of binary includes: for any tiles that have already been masked off during any previous iteration, masking off the tile. For any tiles that have not yet been masked off during any of the previous iterations, a determination is made as to whether a reconstruction error of the tile when reconstructed from binary codes at the previous iterations satisfies an error threshold. When the reconstruction quality satisfies the error threshold, the tile is masked off.
    Type: Application
    Filed: May 16, 2018
    Publication date: October 28, 2021
    Inventors: Michele Covell, Damien Vincent, David Charles Minnen, Saurabh Singh, Sung Jin Hwang, Nicholas Johnston, Joel Eric Shor, George Dan Toderici
  • Publication number: 20200111238
    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.
    Type: Application
    Filed: May 29, 2018
    Publication date: April 9, 2020
    Inventors: Michele Covell, Damien Vincent, David Charles Minnen, Saurabh Singh, Sung Jin Hwang, Nicholas Johnston, Joel Eric Shor, George Dan Toderici