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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
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.
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公开(公告)号：US20210125342A1
公开(公告)日：2021-04-29
申请号：US16949594
申请日：2020-11-05
Applicant: Snap Inc.
Inventor： Yuncheng Li , Linjie Luo , Xuecheng Nie , Ning Zhang
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.
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Patent Agency Ranking
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
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.
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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
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.
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公开(公告)号：US12165335B2
公开(公告)日：2024-12-10
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 , G06V10/764 , G06V10/82 , G06V20/40 , G06V40/20 , G06F3/04817 , H04L51/04 , H04L67/01
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.
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公开(公告)号：US11783494B2
公开(公告)日：2023-10-10
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 , G06V10/764 , G06V10/82 , G06V40/20 , G06F3/04817 , H04L51/04 , H04L67/01
CPC classification number: G06T7/246 , G06T7/73 , G06V10/764 , G06V10/82 , G06V20/46 , G06V40/23 , G06F3/04817 , G06T2200/24 , G06T2207/10016 , G06T2207/20081 , G06T2207/20084 , G06T2207/30196 , H04L51/04 , H04L67/01
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.
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公开(公告)号：US11315259B2
公开(公告)日：2022-04-26
申请号：US16949594
申请日：2020-11-05
Applicant: Snap Inc.
Inventor： Yuncheng Li , Linjie Luo , Xuecheng Nie , Ning Zhang
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.
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