Patents by Inventor Michael Firman

Michael Firman 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).

  • SELF-SUPERVISED TRAINING OF A DEPTH ESTIMATION SYSTEM
    Publication number: 20210314550
    Abstract: A method for training a depth estimation model and methods for use thereof are described. Images are acquired and input into a depth model to extract a depth map for each of the plurality of images based on parameters of the depth model. The method includes inputting the images into a pose decoder to extract a pose for each image. The method includes generating a plurality of synthetic frames based on the depth map and the pose for each image. The method includes calculating a loss value with an input scale occlusion and motion aware loss function based on a comparison of the synthetic frames and the images. The method includes adjusting the plurality of parameters of the depth model based on the loss value. The trained model can receive an image of a scene and generate a depth map of the scene according to the image.
    Type: Application
    Filed: June 22, 2021
    Publication date: October 7, 2021
    Inventors: Clément Godard, Oisin Mac Aodha, Michael Firman, Gabriel J. Brostow
  • Self-supervised training of a depth estimation system
    Patent number: 11082681
    Abstract: A method for training a depth estimation model and methods for use thereof are described. Images are acquired and input into a depth model to extract a depth map for each of the plurality of images based on parameters of the depth model. The method includes inputting the images into a pose decoder to extract a pose for each image. The method includes generating a plurality of synthetic frames based on the depth map and the pose for each image. The method includes calculating a loss value with an input scale occlusion and motion aware loss function based on a comparison of the synthetic frames and the images. The method includes adjusting the plurality of parameters of the depth model based on the loss value. The trained model can receive an image of a scene and generate a depth map of the scene according to the image.
    Type: Grant
    Filed: May 16, 2019
    Date of Patent: August 3, 2021
    Assignee: Niantic, Inc.
    Inventors: Clément Godard, Oisin Mac Aodha, Michael Firman, Gabriel J. Brostow
  • SELF-SUPERVISED TRAINING OF A DEPTH ESTIMATION SYSTEM
    Publication number: 20190356905
    Abstract: A method for training a depth estimation model and methods for use thereof are described. Images are acquired and input into a depth model to extract a depth map for each of the plurality of images based on parameters of the depth model. The method includes inputting the images into a pose decoder to extract a pose for each image. The method includes generating a plurality of synthetic frames based on the depth map and the pose for each image. The method includes calculating a loss value with an input scale occlusion and motion aware loss function based on a comparison of the synthetic frames and the images. The method includes adjusting the plurality of parameters of the depth model based on the loss value. The trained model can receive an image of a scene and generate a depth map of the scene according to the image.
    Type: Application
    Filed: May 16, 2019
    Publication date: November 21, 2019
    Inventors: Clément Godard, Oisin Mac Aodha, Michael Firman, Gabriel J. Brostow