-
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.
-
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:US11790549B2
公开(公告)日:2023-10-17
申请号:US17826849
申请日:2022-05-27
Applicant: Google LLC
Inventor: Reza Mahjourian , Martin Wicke , Anelia Angelova
CPC classification number: G06T7/579 , G06N3/045 , G06N3/084 , G06T7/285 , G06T2207/20081
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.
-
5.
公开(公告)号:US20230297580A1
公开(公告)日:2023-09-21
申请号:US17721873
申请日:2022-04-15
Applicant: Google LLC
Inventor: Sheng Li , Garrett Axel Andersen , Norman Paul Jouppi , Quoc V. Le , Liqun Cheng , Parthasarathy Ranganathan , Julian Paul Grady , Yang Li , Martin Wicke , Yifeng Lu , Yun Ni , Kun Wang
IPC: G06F16/2457 , G06F16/2455 , G06N3/063
CPC classification number: G06F16/2457 , G06F16/24554 , G06N3/063
Abstract: According to various implementations, generally disclosed herein is a hybrid and hierarchical neural architecture search (NAS) approach. The approach includes performing a search space partitioning scheme to divide the search space into sub-search spaces. The approach further includes performing a first type of NAS, such as a Multi-trial NAS, to cover a search across the sub-search spaces. The approach also includes performing a second type of NAS, such as a One-Shot NAS, to cover each sub-search space. The approach further includes automatically stopping the second type of NAS based on one or more early stopping criteria.
-
公开(公告)号:US20210233265A1
公开(公告)日:2021-07-29
申请号:US17150291
申请日:2021-01-15
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: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:US20200258249A1
公开(公告)日:2020-08-13
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.
-
-
-
-
-
-
-
-
-