公开(公告)号：US20210319578A1

公开(公告)日：2021-10-14

申请号：US17272419

申请日：2019-09-05

Applicant: Google LLC

Inventor： Vincent Michael Casser ,  Soeren Pirk ,  Reza Mahjourian ,  Anelia Angelova

IPC: G06T7/55 ,  G06T7/246 ,  G06T3/00 ,  G06N3/08 ,  G06N3/04

Abstract: A system for generating a depth output for an image is described. The system receives input images that depict the same scene, each input image including one or more potential objects. The system generates, for each input image, a respective background image and processes the background images to generate a camera motion output that characterizes the motion of the camera between the input images. For each potential object, the system generates a respective object motion output for the potential object based on the input images and the camera motion output. The system processes a particular input image of the input images using a depth prediction neural network (NN) to generate a depth output for the particular input image, and updates the current values of parameters of the depth prediction NN based on the particular depth output, the camera motion output, and the object motion outputs for the potential objects.

公开(公告)号：US11544498B2

公开(公告)日：2023-01-03

申请号：US17194090

申请日：2021-03-05

Applicant: Google LLC

Inventor： Ariel Gordon ,  Soeren Pirk ,  Anelia Angelova ,  Vincent Michael Casser ,  Yao Lu ,  Anthony Brohan ,  Zhao Chen ,  Jan Dlabal

IPC: G06K9/62 ,  G06N3/04 ,  G06N3/08

Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for training a neural network using consistency measures. One of the methods includes processing a particular training example from a mediator training data set using a first neural network to generate a first output for a first machine learning task; processing the particular training example in the mediator training data set using each of one or more second neural networks, wherein each second neural network is configured to generate a second output for a respective second machine learning task; determining, for each second machine learning task, a consistency target output for the first machine learning task; determining, for each second machine learning task, an error between the first output and the consistency target output corresponding to the second machine learning task; and generating a parameter update for the first neural network from the determined errors.

公开(公告)号：US11783500B2

公开(公告)日：2023-10-10

申请号：US17272419

申请日：2019-09-05

Applicant: Google LLC

Inventor： Vincent Michael Casser ,  Soeren Pirk ,  Reza Mahjourian ,  Anelia Angelova

IPC: G06T7/00 ,  G06T7/55 ,  G06T7/246 ,  G06N3/088 ,  G06T3/00 ,  G06N3/045

CPC classification number: G06T7/55 ,  G06N3/045 ,  G06N3/088 ,  G06T3/0093 ,  G06T7/248 ,  G06T2207/20081 ,  G06T2207/20084

Abstract: A system for generating a depth output for an image is described. The system receives input images that depict the same scene, each input image including one or more potential objects. The system generates, for each input image, a respective background image and processes the background images to generate a camera motion output that characterizes the motion of the camera between the input images. For each potential object, the system generates a respective object motion output for the potential object based on the input images and the camera motion output. The system processes a particular input image of the input images using a depth prediction neural network (NN) to generate a depth output for the particular input image, and updates the current values of parameters of the depth prediction NN based on the particular depth output, the camera motion output, and the object motion outputs for the potential objects.

公开(公告)号：US12260576B2

公开(公告)日：2025-03-25

申请号：US18367888

申请日：2023-09-13

Applicant: Google LLC

Inventor： Vincent Michael Casser ,  Soeren Pirk ,  Reza Mahjourian ,  Anelia Angelova

IPC: G06T7/00 ,  G06N3/045 ,  G06N3/088 ,  G06T3/18 ,  G06T7/246 ,  G06T7/55

Abstract: A system for generating a depth output for an image is described. The system receives input images that depict the same scene, each input image including one or more potential objects. The system generates, for each input image, a respective background image and processes the background images to generate a camera motion output that characterizes the motion of the camera between the input images. For each potential object, the system generates a respective object motion output for the potential object based on the input images and the camera motion output. The system processes a particular input image of the input images using a depth prediction neural network (NN) to generate a depth output for the particular input image, and updates the current values of parameters of the depth prediction NN based on the particular depth output, the camera motion output, and the object motion outputs for the potential objects.

公开(公告)号：US20230419521A1

公开(公告)日：2023-12-28

申请号：US18367888

申请日：2023-09-13

Applicant: Google LLC

Inventor： Vincent Michael Casser ,  Soeren Pirk ,  Reza Mahjourian ,  Anelia Angelova

IPC: G06T7/55 ,  G06T7/246 ,  G06N3/088 ,  G06T3/00 ,  G06N3/045

CPC classification number: G06T7/55 ,  G06T7/248 ,  G06N3/088 ,  G06T3/0093 ,  G06N3/045 ,  G06T2207/20081 ,  G06T2207/20084

Abstract: A system for generating a depth output for an image is described. The system receives input images that depict the same scene, each input image including one or more potential objects. The system generates, for each input image, a respective background image and processes the background images to generate a camera motion output that characterizes the motion of the camera between the input images. For each potential object, the system generates a respective object motion output for the potential object based on the input images and the camera motion output. The system processes a particular input image of the input images using a depth prediction neural network (NN) to generate a depth output for the particular input image, and updates the current values of parameters of the depth prediction NN based on the particular depth output, the camera motion output, and the object motion outputs for the potential objects.

公开(公告)号：US20210279511A1

公开(公告)日：2021-09-09

申请号：US17194090

申请日：2021-03-05

Applicant: Google LLC

Inventor： Ariel Gordon ,  Soeren Pirk ,  Anelia Angelova ,  Vincent Michael Casser ,  Yao Lu ,  Anthony Brohan ,  Zhao Chen ,  Jan Dlabal

IPC: G06K9/62 ,  G06N3/08 ,  G06N3/04

Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for training a neural network using consistency measures. One of the methods includes processing a particular training example from a mediator training data set using a first neural network to generate a first output for a first machine learning task; processing the particular training example in the mediator training data set using each of one or more second neural networks, wherein each second neural network is configured to generate a second output for a respective second machine learning task; determining, for each second machine learning task, a consistency target output for the first machine learning task; determining, for each second machine learning task, an error between the first output and the consistency target output corresponding to the second machine learning task; and generating a parameter update for the first neural network from the determined errors.