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公开(公告)号：US20240161459A1
公开(公告)日：2024-05-16
申请号：US18422887
申请日：2024-01-25
Applicant: Google LLC
Inventor： Matthias Johannes Lorenz Minderer , Alexey Alexeevich Gritsenko , Austin Charles Stone , Dirk Weissenborn , Alexey Dosovitskiy , Neil Matthew Tinmouth Houlsby
IPC: G06V10/764 , G06F40/40 , G06V10/22 , G06V10/74 , G06V10/774 , G06V10/776 , G06V10/82
CPC classification number: G06V10/764 , G06F40/40 , G06V10/225 , G06V10/761 , G06V10/774 , G06V10/776 , G06V10/82
Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for object detection. In one aspect, a method comprises: obtaining: (i) an image, and (ii) a set of one or more query embeddings, wherein each query embedding represents a respective category of object; processing the image and the set of query embeddings using an object detection neural network to generate object detection data for the image, comprising: processing the image using an image encoding subnetwork of the object detection neural network to generate a set of object embeddings; processing each object embedding using a localization subnetwork to generate localization data defining a corresponding region of the image; and processing: (i) the set of object embeddings, and (ii) the set of query embeddings, using a classification subnetwork to generate, for each object embedding, a respective classification score distribution over the set of query embeddings.
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公开(公告)号：US20220108478A1
公开(公告)日：2022-04-07
申请号：US17492537
申请日：2021-10-01
Applicant: Google LLC
Inventor： Neil Matthew Tinmouth Houlsby , Sylvain Gelly , Jakob D. Uszkoreit , Xiaohua Zhai , Georg Heigold , Lucas Klaus Beyer , Alexander Kolesnikov , Matthias Johannes Lorenz Minderer , Dirk Weissenborn , Mostafa Dehghani , Alexey Dosovitskiy , Thomas Unterthiner
Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for processing images using self-attention based neural networks. One of the methods includes obtaining one or more images comprising a plurality of pixels; determining, for each image of the one or more images, a plurality of image patches of the image, wherein each image patch comprises a different subset of the pixels of the image; processing, for each image of the one or more images, the corresponding plurality of image patches to generate an input sequence comprising a respective input element at each of a plurality of input positions, wherein a plurality of the input elements correspond to respective different image patches; and processing the input sequences using a neural network to generate a network output that characterizes the one or more images, wherein the neural network comprises one or more self-attention neural network layers.
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公开(公告)号：US20250148759A1
公开(公告)日：2025-05-08
申请号：US19014029
申请日：2025-01-08
Applicant: Google LLC
Inventor： Matthias Johannes Lorenz Minderer , Alexey Alexeevich Gritsenko , Austin Charles Stone , Dirk Weissenborn , Alexey Dosovitskiy , Neil Matthew Tinmouth Houlsby
IPC: G06V10/764 , G06F40/40 , G06V10/22 , G06V10/74 , G06V10/774 , G06V10/776 , G06V10/82
Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for object detection. In one aspect, a method comprises: obtaining: (i) an image, and (ii) a set of one or more query embeddings, wherein each query embedding represents a respective category of object; processing the image and the set of query embeddings using an object detection neural network to generate object detection data for the image, comprising: processing the image using an image encoding subnetwork of the object detection neural network to generate a set of object embeddings; processing each object embedding using a localization subnetwork to generate localization data defining a corresponding region of the image; and processing: (i) the set of object embeddings, and (ii) the set of query embeddings, using a classification subnetwork to generate, for each object embedding, a respective classification score distribution over the set of query embeddings.
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公开(公告)号：US11983903B2
公开(公告)日：2024-05-14
申请号：US18500034
申请日：2023-11-01
Applicant: Google LLC
Inventor： Neil Matthew Tinmouth Houlsby , Sylvain Gelly , Jakob D. Uszkoreit , Xiaohua Zhai , Georg Heigold , Lucas Klaus Beyer , Alexander Kolesnikov , Matthias Johannes Lorenz Minderer , Dirk Weissenborn , Mostafa Dehghani , Alexey Dosovitskiy , Thomas Unterthiner
CPC classification number: G06T7/97 , G06F18/24 , G06N3/045 , G06N3/08 , G06T2207/20081 , G06T2207/20084
Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for processing images using self-attention based neural networks. One of the methods includes obtaining one or more images comprising a plurality of pixels; determining, for each image of the one or more images, a plurality of image patches of the image, wherein each image patch comprises a different subset of the pixels of the image; processing, for each image of the one or more images, the corresponding plurality of image patches to generate an input sequence comprising a respective input element at each of a plurality of input positions, wherein a plurality of the input elements correspond to respective different image patches; and processing the input sequences using a neural network to generate a network output that characterizes the one or more images, wherein the neural network comprises one or more self-attention neural network layers.
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公开(公告)号：US12230011B2
公开(公告)日：2025-02-18
申请号：US18422887
申请日：2024-01-25
Applicant: Google LLC
Inventor： Matthias Johannes Lorenz Minderer , Alexey Alexeevich Gritsenko , Austin Charles Stone , Dirk Weissenborn , Alexey Dosovitskiy , Neil Matthew Tinmouth Houlsby
IPC: G06K9/00 , G06F40/40 , G06V10/22 , G06V10/74 , G06V10/764 , G06V10/774 , G06V10/776 , G06V10/82
Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for object detection. In one aspect, a method comprises: obtaining: (i) an image, and (ii) a set of one or more query embeddings, wherein each query embedding represents a respective category of object; processing the image and the set of query embeddings using an object detection neural network to generate object detection data for the image, comprising: processing the image using an image encoding subnetwork of the object detection neural network to generate a set of object embeddings; processing each object embedding using a localization subnetwork to generate localization data defining a corresponding region of the image; and processing: (i) the set of object embeddings, and (ii) the set of query embeddings, using a classification subnetwork to generate, for each object embedding, a respective classification score distribution over the set of query embeddings.
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Patent Agency Ranking
公开(公告)号：US20240169715A1
公开(公告)日：2024-05-23
申请号：US18518075
申请日：2023-11-22
Applicant: GOOGLE LLC
Inventor： Lucas Klaus Beyer , Pavel Izmailov , Simon Kornblith , Alexander Kolesnikov , Mathilde Caron , Xiaohua Zhai , Matthias Johannes Lorenz Minderer , Ibrahim Alabdulmohsin , Michael Tobias Tschannen , Filip Pavetic
Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for training a neural network that is configured to process an input image to generate a network output for the input image. In one aspect, a method comprises, at each of a plurality of training steps: obtaining a plurality of training images for the training step; obtaining, for each of the plurality of training images, a respective target output; and selecting, from a plurality of image patch generation schemes, an image patch generation scheme for the training step, wherein, given an input image, each of the plurality of image patch generation schemes generates a different number of patches of the input image, and wherein each patch comprises a respective subset of the pixels of the input image.
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公开(公告)号：US12125247B2
公开(公告)日：2024-10-22
申请号：US17492537
申请日：2021-10-01
Applicant: Google LLC
Inventor： Neil Matthew Tinmouth Houlsby , Sylvain Gelly , Jakob D. Uszkoreit , Xiaohua Zhai , Georg Heigold , Lucas Klaus Beyer , Alexander Kolesnikov , Matthias Johannes Lorenz Minderer , Dirk Weissenborn , Mostafa Dehghani , Alexey Dosovitskiy , Thomas Unterthiner
CPC classification number: G06T7/97 , G06F18/24 , G06N3/045 , G06N3/08 , G06T2207/20081 , G06T2207/20084
Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for processing images using self-attention based neural networks. One of the methods includes obtaining one or more images comprising a plurality of pixels; determining, for each image of the one or more images, a plurality of image patches of the image, wherein each image patch comprises a different subset of the pixels of the image; processing, for each image of the one or more images, the corresponding plurality of image patches to generate an input sequence comprising a respective input element at each of a plurality of input positions, wherein a plurality of the input elements correspond to respective different image patches; and processing the input sequences using a neural network to generate a network output that characterizes the one or more images, wherein the neural network comprises one or more self-attention neural network layers.
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公开(公告)号：US11928854B2
公开(公告)日：2024-03-12
申请号：US18144045
申请日：2023-05-05
Applicant: Google LLC
Inventor： Matthias Johannes Lorenz Minderer , Alexey Alexeevich Gritsenko , Austin Charles Stone , Dirk Weissenborn , Alexey Dosovitskiy , Neil Matthew Tinmouth Houlsby
IPC: G06K9/00 , G06F40/40 , G06V10/22 , G06V10/74 , G06V10/764 , G06V10/774 , G06V10/776 , G06V10/82
CPC classification number: G06V10/764 , G06F40/40 , G06V10/225 , G06V10/761 , G06V10/774 , G06V10/776 , G06V10/82
Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for object detection. In one aspect, a method comprises: obtaining: (i) an image, and (ii) a set of one or more query embeddings, wherein each query embedding represents a respective category of object; processing the image and the set of query embeddings using an object detection neural network to generate object detection data for the image, comprising: processing the image using an image encoding subnetwork of the object detection neural network to generate a set of object embeddings; processing each object embedding using a localization subnetwork to generate localization data defining a corresponding region of the image; and processing: (i) the set of object embeddings, and (ii) the set of query embeddings, using a classification subnetwork to generate, for each object embedding, a respective classification score distribution over the set of query embeddings.
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公开(公告)号：US20240062426A1
公开(公告)日：2024-02-22
申请号：US18500034
申请日：2023-11-01
Applicant: Google LLC
Inventor： Neil Matthew Tinmouth Houlsby , Sylvain Gelly , Jakob D. Uszkoreit , Xiaohua Zhai , Georg Heigold , Lucas Klaus Beyer , Alexander Kolesnikov , Matthias Johannes Lorenz Minderer , Dirk Weissenborn , Mostafa Dehghani , Alexey Dosovitskiy , Thomas Unterthiner
CPC classification number: G06T7/97 , G06F18/24 , G06N3/045 , G06N3/08 , G06T2207/20081 , G06T2207/20084
Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for processing images using self-attention based neural networks. One of the methods includes obtaining one or more images comprising a plurality of pixels; determining, for each image of the one or more images, a plurality of image patches of the image, wherein each image patch comprises a different subset of the pixels of the image; processing, for each image of the one or more images, the corresponding plurality of image patches to generate an input sequence comprising a respective input element at each of a plurality of input positions, wherein a plurality of the input elements correspond to respective different image patches; and processing the input sequences using a neural network to generate a network output that characterizes the one or more images, wherein the neural network comprises one or more self-attention neural network layers.
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公开(公告)号：US20250005798A1
公开(公告)日：2025-01-02
申请号：US18883946
申请日：2024-09-12
Applicant: Google LLC
Inventor： Neil Matthew Tinmouth Houlsby , Sylvain Gelly , Jakob D. Uszkoreit , Xiaohua Zhai , Georg Heigold , Lucas Klaus Beyer , Alexander Kolesnikov , Matthias Johannes Lorenz Minderer , Dirk Weissenborn , Mostafa Dehghani , Alexey Dosovitskiy , Thomas Unterthiner
Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for processing images using self-attention based neural networks. One of the methods includes obtaining one or more images comprising a plurality of pixels; determining, for each image of the one or more images, a plurality of image patches of the image, wherein each image patch comprises a different subset of the pixels of the image; processing, for each image of the one or more images, the corresponding plurality of image patches to generate an input sequence comprising a respective input element at each of a plurality of input positions, wherein a plurality of the input elements correspond to respective different image patches; and processing the input sequences using a neural network to generate a network output that characterizes the one or more images, wherein the neural network comprises one or more self-attention neural network layers.
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