公开(公告)号：US20230064328A1

公开(公告)日：2023-03-02

申请号：US17459964

申请日：2021-08-27

Applicant: Google LLC

Inventor： Colvin Pitts ,  Yukun Zhu ,  Xuhui Jia

IPC: H04L29/06 ,  G06K9/00 ,  G06T11/00 ,  H04N5/272

Abstract: A computing system and method that can be used for safe and privacy preserving video representations of participants in a videoconference. In particular, the present disclosure provides a general pipeline for generating reconstructions of videoconference participants based on semantic statuses and/or activity statuses of the participants. The systems and methods of the present disclosure allow for videoconferences that convey necessary or meaningful information of participants through presentation of generalized representations of participants while filtering unnecessary or unwanted information from the representations by leveraging machine-learning models.

公开(公告)号：US20210081796A1

公开(公告)日：2021-03-18

申请号：US17107745

申请日：2020-11-30

Applicant: Google LLC

Inventor： Barret Zoph ,  Jonathon Shlens ,  Yukun Zhu ,  Maxwell Donald Collins ,  Liang-Chieh Chen ,  Gerhard Florian Schroff ,  Hartwig Adam ,  Georgios Papandreou

IPC: G06N3/08 ,  G06N20/00 ,  G06F17/15 ,  G06K9/62 ,  G06N3/04

Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for determining neural network architectures. One of the methods includes obtaining training data for a dense image prediction task; and determining an architecture for a neural network configured to perform the dense image prediction task, comprising: searching a space of candidate architectures to identify one or more best performing architectures using the training data, wherein each candidate architecture in the space of candidate architectures comprises (i) the same first neural network backbone that is configured to receive an input image and to process the input image to generate a plurality of feature maps and (ii) a different dense prediction cell configured to process the plurality of feature maps and to generate an output for the dense image prediction task; and determining the architecture for the neural network based on the best performing candidate architectures.

公开(公告)号：US10853726B2

公开(公告)日：2020-12-01

申请号：US16425900

申请日：2019-05-29

Applicant: Google LLC

Inventor： Barret Zoph ,  Jonathon Shlens ,  Yukun Zhu ,  Maxwell Donald Emmet Collins ,  Liang-Chieh Chen ,  Gerhard Florian Schroff ,  Hartwig Adam ,  Georgios Papandreou

IPC: G06N3/08 ,  G06N20/00 ,  G06F17/15 ,  G06K9/62 ,  G06N3/04

Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for determining neural network architectures. One of the methods includes obtaining training data for a dense image prediction task; and determining an architecture for a neural network configured to perform the dense image prediction task, comprising: searching a space of candidate architectures to identify one or more best performing architectures using the training data, wherein each candidate architecture in the space of candidate architectures comprises (i) the same first neural network backbone that is configured to receive an input image and to process the input image to generate a plurality of feature maps and (ii) a different dense prediction cell configured to process the plurality of feature maps and to generate an output for the dense image prediction task; and determining the architecture for the neural network based on the best performing candidate architectures.