公开(公告)号：US20240062335A1

公开(公告)日：2024-02-22

申请号：US18499866

申请日：2023-11-01

Applicant: Snap Inc.

Inventor： Guohui Wang ,  Sumant Milind Hanumante ,  Ning Xu ,  Yuncheng Li

IPC: G06T3/40 ,  G06N3/08 ,  G06N3/04 ,  G06T1/20 ,  G06T11/60 ,  G06N3/063

CPC classification number: G06T3/4046 ,  G06N3/08 ,  G06N3/04 ,  G06T1/20 ,  G06T11/60 ,  G06N3/063 ,  G06T2207/20081

Abstract: Remote distribution of multiple neural network models to various client devices over a network can be implemented by identifying a native neural network and remotely converting the native neural network to a target neural network based on a given client device operating environment. The native neural network can be configured for execution using efficient parameters, and the target neural network can use less efficient but more precise parameters.

公开(公告)号：US11880509B2

公开(公告)日：2024-01-23

申请号：US18151857

申请日：2023-01-09

Applicant: Snap Inc.

Inventor： Yuncheng Li ,  Jonathan M. Rodriguez, II ,  Zehao Xue ,  Yingying Wang

IPC: G06F3/01 ,  G06T7/73 ,  G06T7/20 ,  H04N13/204 ,  G06V40/10 ,  G06F18/214 ,  G06V10/764 ,  G06V10/774 ,  G06V10/82 ,  G06V10/26

CPC classification number: G06F3/017 ,  G06F3/011 ,  G06F18/214 ,  G06T7/20 ,  G06T7/73 ,  G06V10/267 ,  G06V10/764 ,  G06V10/774 ,  G06V10/82 ,  G06V40/11 ,  H04N13/204 ,  G06T2207/10012 ,  G06T2207/20081 ,  G06T2207/20084 ,  G06T2207/20132 ,  G06T2207/30196

Abstract: Systems and methods herein describe using a neural network to identify a first set of joint location coordinates and a second set of joint location coordinates and identifying a three-dimensional hand pose based on both the first and second sets of joint location coordinates.

公开(公告)号：US11755910B2

公开(公告)日：2023-09-12

申请号：US17878591

申请日：2022-08-01

Applicant: Snap Inc.

Inventor： Yuncheng Li ,  Zhou Ren ,  Ning Xu ,  Enxu Yan ,  Tan Yu

IPC: G06N3/08 ,  G06T7/55 ,  G06T7/33 ,  G06V20/64 ,  G06F18/214 ,  G06F18/2431 ,  G06V10/82 ,  G06V10/44 ,  G06V20/20 ,  G06V20/40

CPC classification number: G06N3/08 ,  G06F18/214 ,  G06F18/2431 ,  G06T7/344 ,  G06T7/55 ,  G06V10/454 ,  G06V10/82 ,  G06V20/20 ,  G06V20/41 ,  G06V20/64

Abstract: Systems and methods are disclosed for capturing multiple sequences of views of a three-dimensional object using a plurality of virtual cameras. The systems and methods generate aligned sequences from the multiple sequences based on an arrangement of the plurality of virtual cameras in relation to the three-dimensional object. Using a convolutional network, the systems and methods classify the three-dimensional object based on the aligned sequences and identify the three-dimensional object using the classification.

公开(公告)号：US20230010480A1

公开(公告)日：2023-01-12

申请号：US17660462

申请日：2022-04-25

Applicant: Snap, Inc.

Inventor： Yuncheng Li ,  Linjie Luo ,  Xuecheng Nie ,  Ning Zhang

IPC: G06T7/246 ,  G06T7/73 ,  G06V20/40

Abstract: Systems, devices, media and methods are presented for a human pose tracking framework. The human pose tracking framework may identify a message with video frames, generate, using a composite convolutional neural network, joint data representing joint locations of a human depicted in the video frames, the generating of the joint data by the composite convolutional neural network done by a deep convolutional neural network operating on one portion of the video frames, a shallow convolutional neural network operating on a another portion of the video frames, and tracking the joint locations using a one-shot learner neural network that is trained to track the joint locations based on a concatenation of feature maps and a convolutional pose machine. The human pose tracking framework may store, the joint locations, and cause presentation of a rendition of the joint locations on a user interface of a client device.

公开(公告)号：US20220230277A1

公开(公告)日：2022-07-21

申请号：US17714764

申请日：2022-04-06

Applicant: Snap Inc.

Inventor： Guohui Wang ,  Sumant Milind Hanumante ,  Ning Xu ,  Yuncheng Li

IPC: G06T3/40 ,  G06N3/08 ,  G06N3/04 ,  G06T1/20 ,  G06T11/60 ,  G06N3/063

Abstract: Remote distribution of multiple neural network models to various client devices over a network can be implemented by identifying a native neural network and remotely converting the native neural network to a target neural network based on a given client device operating environment. The native neural network can be configured for execution using efficient parameters, and the target neural network can use less efficient but more precise parameters.

公开(公告)号：US11182603B1

公开(公告)日：2021-11-23

申请号：US16450376

申请日：2019-06-24

Applicant: Snap Inc.

Inventor： Yuncheng Li ,  Linjie Yang ,  Ning Zhang ,  Zhengyuan Yang

IPC: G06K9/00 ,  G06F17/15 ,  G06N3/04 ,  G06T7/136

Abstract: Segmentation of an image into individual body parts is performed based on a trained model. The model is trained with a plurality of training images, each training image representing a corresponding training figure. The model is also trained with a corresponding plurality of segmentations of the training figures. Each segmentation is generated by positioning body parts between defined positions of joints of the represented figure. The body parts are represented by body part templates obtained from a template library, with the templates defining characteristics of body parts represented by the templates.

公开(公告)号：US10861170B1

公开(公告)日：2020-12-08

申请号：US16206684

申请日：2018-11-30

Applicant: Snap Inc.

Inventor： Yuncheng Li ,  Linjie Luo ,  Xuecheng Nie ,  Ning Zhang

IPC: G06T7/246 ,  G06T7/73 ,  G06K9/00 ,  H04L29/06 ,  G06F3/0481 ,  H04L12/58

Abstract: Systems, devices, media and methods are presented for a human pose tracking framework. The human pose tracking framework may identify a message with video frames, generate, using a composite convolutional neural network, joint data representing joint locations of a human depicted in the video frames, the generating of the joint data by the composite convolutional neural network done by a deep convolutional neural network operating on one portion of the video frames, a shallow convolutional neural network operating on a another portion of the video frames, and tracking the joint locations using a one-shot learner neural network that is trained to track the joint locations based on a concatenation of feature maps and a convolutional pose machine. The human pose tracking framework may store, the joint locations, and cause presentation of a rendition of the joint locations on a user interface of a client device.

公开(公告)号：US20250029308A1

公开(公告)日：2025-01-23

申请号：US18905209

申请日：2024-10-03

Applicant: Snap Inc.

Inventor： Avihay Assouline ,  Itamar Berger ,  Yuncheng Li

IPC: G06T13/40 ,  G06V40/10

Abstract: Aspects of the present disclosure involve a system comprising a computer-readable storage medium storing a program and a method for detecting a pose of a user. The program and method include receiving a monocular image that includes a depiction of a body of a user; detecting a plurality of skeletal joints of the body depicted in the monocular image; and determining a pose represented by the body depicted in the monocular image based on the detected plurality of skeletal joints of the body. A pose of an avatar is modified to match the pose represented by the body depicted in the monocular image by adjusting a set of skeletal joints of a rig of an avatar based on the detected plurality of skeletal joints of the body; and the avatar having the modified pose that matches the pose represented by the body depicted in the monocular image is generated for display.

公开(公告)号：US12033078B2

公开(公告)日：2024-07-09

申请号：US18230499

申请日：2023-08-04

Applicant: Snap Inc.

Inventor： Yuncheng Li ,  Zhou Ren ,  Ning Xu ,  Enxu Yan ,  Tan Yu

IPC: G06N3/08 ,  G06F18/214 ,  G06F18/2431 ,  G06T7/33 ,  G06T7/55 ,  G06V10/44 ,  G06V10/82 ,  G06V20/20 ,  G06V20/40 ,  G06V20/64

CPC classification number: G06N3/08 ,  G06F18/214 ,  G06F18/2431 ,  G06T7/344 ,  G06T7/55 ,  G06V10/454 ,  G06V10/82 ,  G06V20/20 ,  G06V20/41 ,  G06V20/64

Abstract: Systems and methods are disclosed for capturing multiple sequences of views of a three-dimensional object using a plurality of virtual cameras. The systems and methods generate aligned sequences from the multiple sequences based on an arrangement of the plurality of virtual cameras in relation to the three-dimensional object. Using a convolutional network, the systems and methods classify the three-dimensional object based on the aligned sequences and identify the three-dimensional object using the classification.

公开(公告)号：US20240062390A1

公开(公告)日：2024-02-22

申请号：US18460335

申请日：2023-09-01

Applicant: Snap Inc.

Inventor： Yuncheng Li ,  Linjie Luo ,  Xuecheng Nie ,  Ning Zhang

IPC: G06T7/246 ,  G06T7/73 ,  G06V20/40 ,  G06V10/764 ,  G06V10/82 ,  G06V40/20

CPC classification number: G06T7/246 ,  G06T7/73 ,  G06V20/46 ,  G06V10/764 ,  G06V10/82 ,  G06V40/23 ,  G06T2207/10016 ,  G06T2207/20084 ,  G06T2207/20081 ,  G06F3/04817

Abstract: Systems, devices, media and methods are presented for a human pose tracking framework. The human pose tracking framework may identify a message with video frames, generate, using a composite convolutional neural network, joint data representing joint locations of a human depicted in the video frames, the generating of the joint data by the composite convolutional neural network done by a deep convolutional neural network operating on one portion of the video frames, a shallow convolutional neural network operating on a another portion of the video frames, and tracking the joint locations using a one-shot learner neural network that is trained to track the joint locations based on a concatenation of feature maps and a convolutional pose machine. The human pose tracking framework may store, the joint locations, and cause presentation of a rendition of the joint locations on a user interface of a client device.