公开(公告)号：US20240338515A1

公开(公告)日：2024-10-10

申请号：US18296059

申请日：2023-04-05

Applicant: Google LLC

Inventor： Spencer S. Johnson ,  Calvin Cheng ,  David Francis Pomeroy ,  Yucheng Wang ,  Ranmin Chen ,  Alexander Mermelstein ,  Lingxing Yuan ,  Sara Christine Adkins ,  An-Tai Li ,  Wenchao Tong ,  Priscilla Pun ,  Brendan Khoi Luu

IPC: G06F40/143

CPC classification number: G06F40/143

Abstract: Example embodiments of the present disclosure provide for an example method including obtaining a request for third party content elements to be used in a publisher-rendered native content item slot. The example method includes obtaining input signals comprising data indicative of publisher-rendered native content items. The example method includes generating, by a model associated with the content provider computing system, based on the input signals, an expected native content item slot size. The example method includes obtaining, by the content provider computing system, content item elements from a content provider. The example method includes generating based on the expected native content item slot size, a replacement main asset comprising a first content element of the one or more content elements. The example method includes transmitting data including the replacement main asset and additional content elements to a publisher to be used in a publisher-rendered native content item slot.

公开(公告)号：US12236676B2

公开(公告)日：2025-02-25

申请号：US17438687

申请日：2019-07-19

Applicant: Google LLC

Inventor： Mikael Pierre Bonnevie ,  Aaron Maschinot ,  Aaron Sarna ,  Shuchao Bi ,  Jingbin Wang ,  Michael Spencer Krainin ,  Wenchao Tong ,  Dilip Krishnan ,  Haifeng Gong ,  Ce Liu ,  Hossein Talebi ,  Raanan Sayag ,  Piotr Teterwak

IPC: G06K9/00 ,  G06N3/045 ,  G06T7/10 ,  G06V10/82

Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for generating realistic extensions of images. In one aspect, a method comprises providing an input that comprises a provided image to a generative neural network having a plurality of generative neural network parameters. The generative neural network processes the input in accordance with trained values of the plurality of generative neural network parameters to generate an extended image. The extended image has (i) more rows, more columns, or both than the provided image, and (ii) is predicted to be a realistic extension of the provided image. The generative neural network is trained using an adversarial loss objective function.

公开(公告)号：US20250077710A1

公开(公告)日：2025-03-06

申请号：US18285297

申请日：2022-12-12

Applicant: Google LLC

Inventor： Gang Wang ,  Wenchao Tong

IPC: G06F21/62 ,  G06F40/14

Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for generating dynamic digital content in privacy preserving ways are described. In one aspect, a method includes receiving, by a trusted server and from multiple content platforms, digital component data for digital components. The server received, from each content platform, dynamic content selection logic for selecting discrete content elements for digital components of the content platform. The server selects, from digital components for which digital component data is stored in a digital component repository, candidate digital components based at least on user data included in a digital component request. For each candidate digital component, the server executes the dynamic content selection logic of the content platform that provided the digital component data for the candidate digital component, the executing resulting in selection of a particular layout and a particular subset of content elements for the digital component.

公开(公告)号：US20220148299A1

公开(公告)日：2022-05-12

申请号：US17438687

申请日：2019-07-19

Applicant: Google LLC

Inventor： Mikael Pierre Bonnevie ,  Aaron Maschinot ,  Aaron Sarna ,  Shuchao Bi ,  Jingbin Wang ,  Michael Spencer Krainin ,  Wenchao Tong ,  Dilip Krishnan ,  Haifeng Gong ,  Ce Liu ,  Hossein Talebi ,  Raanan Sayag ,  Piotr Teterwak

IPC: G06V10/82 ,  G06N3/04 ,  G06T7/10

Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for generating realistic extensions of images. In one aspect, a method comprises providing an input that comprises a provided image to a generative neural network having a plurality of generative neural network parameters. The generative neural network processes the input in accordance with trained values of the plurality of generative neural network parameters to generate an extended image. The extended image has (i) more rows, more columns, or both than the provided image, and (ii) is predicted to be a realistic extension of the provided image. The generative neural network is trained using an adversarial loss objective function.