Patents by Inventor Steve Branson

Steve Branson 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).

  • Machine-learning based video compression
    Patent number: 10860929
    Abstract: An encoder system trains a compression model that includes an autoencoder model and a frame extractor model. The encoding portion of the autoencoder is coupled to receive a set of target frames and a previous state tensor for the set of target frames and generate compressed code. The decoding portion of the autoencoder is coupled to receive the compressed code and the previous state tensor for the set of frames and generate a next state tensor for the set of target frames. The frame extractor model is coupled to receive the next state tensor and generate a set of reconstructed frames that correspond to the set of target frames by performing one or more operations on the state tensor. The state tensor for the set of frames includes information from frames of the video that can be used by the frame extractor to generate reconstructed frames.
    Type: Grant
    Filed: May 11, 2020
    Date of Patent: December 8, 2020
    Assignee: WaveOne Inc.
    Inventors: Oren Rippel, Sanjay Nair, Carissa Lew, Steve Branson, Alexander Anderson, Lubomir Bourdev
  • Machine-Learning Based Video Compression
    Publication number: 20200272903
    Abstract: An encoder system trains a compression model that includes an autoencoder model and a frame extractor model. The encoding portion of the autoencoder is coupled to receive a set of target frames and a previous state tensor for the set of target frames and generate compressed code. The decoding portion of the autoencoder is coupled to receive the compressed code and the previous state tensor for the set of frames and generate a next state tensor for the set of target frames. The frame extractor model is coupled to receive the next state tensor and generate a set of reconstructed frames that correspond to the set of target frames by performing one or more operations on the state tensor. The state tensor for the set of frames includes information from frames of the video that can be used by the frame extractor to generate reconstructed frames.
    Type: Application
    Filed: May 11, 2020
    Publication date: August 27, 2020
    Inventors: Oren Rippel, Sanjay Nair, Carissa Lew, Steve Branson, Alexander Anderson, Lubomir Bourdev
  • Machine-learning based video compression
    Patent number: 10685282
    Abstract: An encoder system trains a compression model that includes an autoencoder model and a frame extractor model. The encoding portion of the autoencoder is coupled to receive a set of target frames and a previous state tensor for the set of target frames and generate compressed code. The decoding portion of the autoencoder is coupled to receive the compressed code and the previous state tensor for the set of frames and generate a next state tensor for the set of target frames. The frame extractor model is coupled to receive the next state tensor and generate a set of reconstructed frames that correspond to the set of target frames by performing one or more operations on the state tensor. The state tensor for the set of frames includes information from frames of the video that can be used by the frame extractor to generate reconstructed frames.
    Type: Grant
    Filed: November 7, 2018
    Date of Patent: June 16, 2020
    Assignee: WaveOne Inc.
    Inventors: Oren Rippel, Sanjay Nair, Carissa Lew, Steve Branson, Alexander Anderson, Lubomir Bourdev
  • Machine-Learning Based Video Compression
    Publication number: 20200036995
    Abstract: An encoder system trains a compression model that includes an autoencoder model and a frame extractor model. The encoding portion of the autoencoder is coupled to receive a set of target frames and a previous state tensor for the set of target frames and generate compressed code. The decoding portion of the autoencoder is coupled to receive the compressed code and the previous state tensor for the set of frames and generate a next state tensor for the set of target frames. The frame extractor model is coupled to receive the next state tensor and generate a set of reconstructed frames that correspond to the set of target frames by performing one or more operations on the state tensor. The state tensor for the set of frames includes information from frames of the video that can be used by the frame extractor to generate reconstructed frames.
    Type: Application
    Filed: November 7, 2018
    Publication date: January 30, 2020
    Inventors: Oren Rippel, Sanjay Nair, Carissa Lew, Steve Branson, Alexander Anderson, Lubomir Bourdev