-
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
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：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
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：US10929996B2
公开(公告)日：2021-02-23
申请号：US16332991
申请日：2017-09-12
Applicant: Google LLC
Inventor： Anelia Angelova , Martin Wicke , Reza Mahjourian
Abstract: A system includes an image depth prediction neural network implemented by one or more computers. The image depth prediction neural network is a recurrent neural network that is configured to receive a sequence of images and, for each image in the sequence: process the image in accordance with a current internal state of the recurrent neural network to (i) update the current internal state and (ii) generate a depth output that characterizes a predicted depth of a future image in the sequence.
-
公开(公告)号：US10810752B2
公开(公告)日：2020-10-20
申请号：US16861441
申请日：2020-04-29
Applicant: Google LLC
Inventor： Anelia Angelova , Martin Wicke , Reza Mahjourian
Abstract: A system includes a neural network implemented by one or more computers, in which the neural network includes an image depth prediction neural network and a camera motion estimation neural network. The neural network is configured to receive a sequence of images. The neural network is configured to process each image in the sequence of images using the image depth prediction neural network to generate, for each image, a respective depth output that characterizes a depth of the image, and to process a subset of images in the sequence of images using the camera motion estimation neural network to generate a camera motion output that characterizes the motion of a camera between the images in the subset. The image depth prediction neural network and the camera motion estimation neural network have been jointly trained using an unsupervised learning technique.
-
公开(公告)号：US20190279383A1
公开(公告)日：2019-09-12
申请号：US16332991
申请日：2017-09-12
Applicant: Google LLC
Inventor： Anelia Angelova , Martin Wicke , Reza Mahjourian
Abstract: A system includes an image depth prediction neural network implemented by one or more computers. The image depth prediction neural network is a recurrent neural network that is configured to receive a sequence of images and, for each image in the sequence: process the image in accordance with a current internal state of the recurrent neural network to (i) update the current internal state and (ii) generate a depth output that characterizes a predicted depth of a future image in the sequence.
-
Patent Agency Ranking
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
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：US11734847B2
公开(公告)日：2023-08-22
申请号：US17150291
申请日：2021-01-15
Applicant: Google LLC
Inventor： Anelia Angelova , Martin Wicke , Reza Mahjourian
CPC classification number: G06T7/55 , G06N3/044 , G06N3/045 , G06N3/08 , G06T3/40 , G06T15/205 , G06T7/579 , G06T2207/10016 , G06T2207/10028 , G06T2207/20084 , G06T2207/30244
Abstract: A system includes an image depth prediction neural network implemented by one or more computers. The image depth prediction neural network is a recurrent neural network that is configured to receive a sequence of images and, for each image in the sequence: process the image in accordance with a current internal state of the recurrent neural network to (i) update the current internal state and (ii) generate a depth output that characterizes a predicted depth of a future image in the sequence.
-
公开(公告)号：US20220292701A1
公开(公告)日：2022-09-15
申请号：US17826849
申请日：2022-05-27
Applicant: Google LLC
Inventor： Reza Mahjourian , Martin Wicke , Anelia Angelova
Abstract: A system includes a neural network implemented by one or more computers, in which the neural network includes an image depth prediction neural network and a camera motion estimation neural network. The neural network is configured to receive a sequence of images. The neural network is configured to process each image in the sequence of images using the image depth prediction neural network to generate, for each image, a respective depth output that characterizes a depth of the image, and to process a subset of images in the sequence of images using the camera motion estimation neural network to generate a camera motion output that characterizes the motion of a camera between the images in the subset. The image depth prediction neural network and the camera motion estimation neural network have been jointly trained using an unsupervised learning technique.
-
公开(公告)号：US11348268B2
公开(公告)日：2022-05-31
申请号：US17010967
申请日：2020-09-03
Applicant: Google LLC
Inventor： Reza Mahjourian , Martin Wicke , Anelia Angelova
Abstract: A system includes a neural network implemented by one or more computers, in which the neural network includes an image depth prediction neural network and a camera motion estimation neural network. The neural network is configured to receive a sequence of images. The neural network is configured to process each image in the sequence of images using the image depth prediction neural network to generate, for each image, a respective depth output that characterizes a depth of the image, and to process a subset of images in the sequence of images using the camera motion estimation neural network to generate a camera motion output that characterizes the motion of a camera between the images in the subset. The image depth prediction neural network and the camera motion estimation neural network have been jointly trained using an unsupervised learning technique.
-
公开(公告)号：US20210073997A1
公开(公告)日：2021-03-11
申请号：US16562819
申请日：2019-09-06
Applicant: Google LLC
Inventor： Suhani Vora , Reza Mahjourian , Soeren Pirk , Anelia Angelova
Abstract: This disclosure describes a system including one or more computers and one or more non-transitory storage devices storing instructions that, when executed by one or more computers, cause the one or more computers to perform operations for generating a predicted segmentation map for potential objects in a future scene depicted in a future image. The operations includes: receiving a sequence of input images that depict the same scene, the input images being captured by a camera at different time steps, the sequence of input images comprising a current input image and one or more input images preceding the current image in the sequence; processing the current input image to generate a segmentation map for potential objects in the current input image and a respective depth map for the current input image; generating a point cloud for the current input image using the segmentation map and the depth map of the current input image, wherein the point cloud is a 3-dimensional (3D) structure representation of the scene as depicted in the current input image; processing the sequence of input images using an ego-motion estimation neural network to generate, for each pair of two consecutive input images in the sequence, a respective ego-motion output that characterizes motion of the camera between the two consecutive input images; processing the ego-motion outputs using a future ego-motion prediction neural network to generate a future ego-motion output that is a prediction of future motion of the camera from the current input image in the sequence to a future image, wherein the future image is an image that would be captured by the camera at a future time step; processing the point cloud of the current input image and the future ego-motion output to generate a future point cloud that is a predicted 3D representation of a future scene as depicted in the future image; and processing the future point cloud to generate a predicted segmentation map for potential objects in the future scene depicted in the future image.
-
-
-
-
-
-
-
-
-
Search Results
15
records
(took 0.015 seconds)
