公开(公告)号：US20240380865A1

公开(公告)日：2024-11-14

申请号：US18316136

申请日：2023-05-11

Applicant: Google LLC

Inventor： Jamie Menjay Lin ,  Yu-Hui Chen

IPC: H04N7/15 ,  G06F3/04842 ,  G06V10/56 ,  G06V10/74 ,  H04N7/14

Abstract: Methods and systems for user-selected viewpoint rendering of a virtual meeting are provided herein. First image data generated by a first client device during a virtual meeting and second image data generated by a second client device during a virtual meeting is obtained. The first image data depicts object(s) captured from a first vantage point and the second image data depicts the object(s) captured from a second vantage point. A request is received from a third client device for third image data depicting the object(s) captured from a third vantage point. The third image data depicting the object(s) corresponding to the third vantage point is generated based on the first image data and the second image data. A rendering of the third image data is provided for presentation via a graphical user interface (GUI) of the third client device during the virtual meeting in accordance with the request.

公开(公告)号：US20240412334A1

公开(公告)日：2024-12-12

申请号：US18735050

申请日：2024-06-05

Applicant: Google LLC

Inventor： Raman Sarokin ,  Yu-Hui Chen ,  Juhyun Lee ,  Jiuqiang Tang ,  Chuo-Ling Chang ,  Andrei Kulik ,  Matthias Grundmann

IPC: G06T5/60 ,  G06T1/20 ,  G06T5/70

Abstract: Systems, methods, devices, and related techniques for accelerating execution of diffusion models or of other neural networks that involve similar operations. Some aspects include accelerating inference computations in neural networks, including inference computations utilized in denoising (also referred to as “diffusion”) neural networks.

公开(公告)号：US12216999B2

公开(公告)日：2025-02-04

申请号：US17432259

申请日：2020-02-19

Applicant: Google LLC

Inventor： Nan Du ,  Linh Mai Tran ,  Yu-Hui Chen ,  Izhak Shafran

IPC: G06F40/279 ,  G06F40/284 ,  G06F40/295 ,  G06N3/045

Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for extracting entities from conversation transcript data. One of the methods includes obtaining a conversation transcript sequence, processing the conversation transcript sequence using a span detection neural network configured to generate a set of text token spans; and for each text token span: processing a span representation using an entity name neural network to generate an entity name probability distribution over a set of entity names, each probability in the entity name probability distribution representing a likelihood that a corresponding entity name is a name of the entity referenced by the text token span; and processing the span representation using an entity status neural network to generate an entity status probability distribution over a set of entity statuses.