公开(公告)号：US20250005797A1

公开(公告)日：2025-01-02

申请号：US18883917

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

IPC: G06T7/00 ,  G06F18/24 ,  G06N3/045 ,  G06N3/08

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.

公开(公告)号：US20230360365A1

公开(公告)日：2023-11-09

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: G06V10/764 ,  G06F40/40 ,  G06V10/82 ,  G06V10/22 ,  G06V10/774 ,  G06V10/776 ,  G06V10/74

CPC classification number: G06V10/764 ,  G06F40/40 ,  G06V10/82 ,  G06V10/225 ,  G06V10/774 ,  G06V10/776 ,  G06V10/761

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.