公开(公告)号：US20230274532A1

公开(公告)日：2023-08-31

申请号：US18313772

申请日：2023-05-08

Applicant: Google LLC

Inventor： Jon Shlens ,  Ekin Dogus Cubuk ,  Quoc Le ,  Tsung-Yi Lin ,  Barret Zoph ,  Golnaz Ghiasi

IPC: G06V10/772 ,  G06T3/60 ,  G06T3/20 ,  G06T11/00 ,  G06F18/24 ,  G06F18/21

CPC classification number: G06V10/772 ,  G06F18/217 ,  G06F18/24 ,  G06T3/20 ,  G06T3/60 ,  G06T11/001

Abstract: Example aspects of the present disclosure are directed to systems and methods for learning data augmentation strategies for improved object detection model performance. In particular, example aspects of the present disclosure are directed to iterative reinforcement learning approaches in which, at each of a plurality of iterations, a controller model selects a series of one or more augmentation operations to be applied to training images to generate augmented images. For example, the controller model can select the augmentation operations from a defined search space of available operations which can, for example, include operations that augment the training image without modification of the locations of a target object and corresponding bounding shape within the image and/or operations that do modify the locations of the target object and bounding shape within the training image.

公开(公告)号：US20220215682A1

公开(公告)日：2022-07-07

申请号：US17702438

申请日：2022-03-23

Applicant: Google LLC

Inventor： Jon Shlens ,  Ekin Dogus Cubuk ,  Quoc Le ,  Tsung-Yi Lin ,  Barret Zoph ,  Golnaz Ghiasi

IPC: G06V30/194 ,  G06K9/62 ,  G06T3/60 ,  G06T3/20 ,  G06T11/00

Abstract: Example aspects of the present disclosure are directed to systems and methods for learning data augmentation strategies for improved object detection model performance. In particular, example aspects of the present disclosure are directed to iterative reinforcement learning approaches in which, at each of a plurality of iterations, a controller model selects a series of one or more augmentation operations to be applied to training images to generate augmented images. For example, the controller model can select the augmentation operations from a defined search space of available operations which can, for example, include operations that augment the training image without modification of the locations of a target object and corresponding bounding shape within the image and/or operations that do modify the locations of the target object and bounding shape within the training image.

公开(公告)号：US20240378509A1

公开(公告)日：2024-11-14

申请号：US18784068

申请日：2024-07-25

Applicant: Google LLC

Inventor： Xianzhi Du ,  Yin Cui ,  Tsung-Yi Lin ,  Quoc V. Le ,  Pengchong Jin ,  Mingxing Tan ,  Golnaz Ghiasi ,  Xiaodan Song

IPC: G06N20/00 ,  G06F11/34 ,  G06N3/04

Abstract: A computer-implemented method of generating scale-permuted models can generate models having improved accuracy and reduced evaluation computational requirements. The method can include defining, by a computing system including one or more computing devices, a search space including a plurality of candidate permutations of a plurality of candidate feature blocks, each of the plurality of candidate feature blocks having a respective scale. The method can include performing, by the computing system, a plurality of search iterations by a search algorithm to select a scale-permuted model from the search space, the scale-permuted model based at least in part on a candidate permutation of the plurality of candidate permutations.

公开(公告)号：US12136262B2

公开(公告)日：2024-11-05

申请号：US18379532

申请日：2023-10-12

Applicant: Google LLC

Inventor： Weicheng Kuo ,  Anelia Angelova ,  Tsung-Yi Lin

IPC: G06V10/82 ,  G06T7/10 ,  G06V10/25 ,  G06V10/26 ,  G06V10/44 ,  G06V10/764 ,  G06V10/77 ,  G06V10/774 ,  G06V20/10

Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for performing instance segmentation by detecting and segmenting individual objects in an image. In one aspect, a method comprises: processing an image to generate data identifying a region of the image that depicts a particular object; obtaining data defining a plurality of example object segmentations; generating a respective weight value for each of the example object segmentations; for each of a plurality of pixels in the region of the image, determining a score characterizing a likelihood that the pixel is included in the particular object depicted in the region of the image using: (i) the example object segmentations, and (ii) the weight values for the example object segmentations; and generating a segmentation of the particular object depicted in the region of the image using the scores for the pixels in the region of the image.

公开(公告)号：US12080055B2

公开(公告)日：2024-09-03

申请号：US17697750

申请日：2022-03-17

Applicant: Google LLC

Inventor： Tsung-Yi Lin ,  Barret Zoph ,  Ekin Dogus Cubuk ,  Golnaz Ghiasi ,  Quoc V. Le

IPC: G06V10/82 ,  G06N3/084 ,  G06V10/764 ,  G06V10/77 ,  G06V10/774 ,  G06V10/776 ,  G06V10/80

CPC classification number: G06V10/82 ,  G06N3/084 ,  G06V10/764 ,  G06V10/7715 ,  G06V10/774 ,  G06V10/776 ,  G06V10/806

Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for training an image representation neural network.

公开(公告)号：US12079695B2

公开(公告)日：2024-09-03

申请号：US17061355

申请日：2020-10-01

Applicant: Google LLC

Inventor： Xianzhi Du ,  Yin Cui ,  Tsung-Yi Lin ,  Quoc V. Le ,  Pengchong Jin ,  Mingxing Tan ,  Golnaz Ghiasi ,  Xiaodan Song

IPC: G06N20/00 ,  G06F11/34 ,  G06N3/04

CPC classification number: G06N20/00 ,  G06F11/3495 ,  G06N3/04

Abstract: A computer-implemented method of generating scale-permuted models can generate models having improved accuracy and reduced evaluation computational requirements. The method can include defining, by a computing system including one or more computing devices, a search space including a plurality of candidate permutations of a plurality of candidate feature blocks, each of the plurality of candidate feature blocks having a respective scale. The method can include performing, by the computing system, a plurality of search iterations by a search algorithm to select a scale-permuted model from the search space, the scale-permuted model based at least in part on a candidate permutation of the plurality of candidate permutations.

公开(公告)号：US20210374453A1

公开(公告)日：2021-12-02

申请号：US17290814

申请日：2019-08-14

Applicant: Google LLC

Inventor： Weicheng Kuo ,  Anelia Angelova ,  Tsung-Yi Lin

IPC: G06K9/34 ,  G06K9/62 ,  G06K9/32 ,  G06K9/46 ,  G06N3/02

Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for performing instance segmentation by detecting and segmenting individual objects in an image. In one aspect, a method comprises: processing an image to generate data identifying a region of the image that depicts a particular object; obtaining data defining a plurality of example object segmentations; generating a respective weight value for each of the example object segmentations; for each of a plurality of pixels in the region of the image, determining a score characterizing a likelihood that the pixel is included in the particular object depicted in the region of the image using: (i) the example object segmentations, and (ii) the weight values for the example object segmentations; and generating a segmentation of the particular object depicted in the region of the image using the scores for the pixels in the region of the image.