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公开(公告)号：US10395100B1
公开(公告)日：2019-08-27
申请号：US16226084
申请日：2018-12-19
Applicant: Snap Inc.
Inventor： Jia Li , Xutao Lv , Xiaoyu Wang , Xuehan Xiong , Jianchao Yang
Abstract: Systems, devices, media, and methods are presented for modeling facial representations using image segmentation with a client device. The systems and methods receive an image depicting a face, detect at least a portion of the face within the image, and identify a set of facial features within the portion of the face. The systems and methods generate a descriptor function representing the set of facial features, fit object functions of the descriptor function, identify an identification probability for each facial feature, and assign an identification to each facial feature.
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公开(公告)号：US20190087660A1
公开(公告)日：2019-03-21
申请号：US15706096
申请日：2017-09-15
Applicant: Snap Inc.
Inventor： Samuel Edward Hare , Fedir Poliakov , Guohui Wang , Xuehan Xiong , Jianchao Yang , Linjie Yang , Shah Tanmay Anilkumar
Abstract: A mobile device can generate real-time complex visual image effects using asynchronous processing pipeline. A first pipeline applies a complex image process, such as a neural network, to keyframes of a live image sequence. A second pipeline generates flow maps that describe feature transformations in the image sequence. The flow maps can be used to process non-keyframes on the fly. The processed keyframes and non-keyframes can be used to display a complex visual effect on the mobile device in real-time or near real-time.
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公开(公告)号：US10198626B2
公开(公告)日：2019-02-05
申请号：US15297789
申请日：2016-10-19
Applicant: Snap Inc.
Inventor： Jia Li , Xutao Lv , Xiaoyu Wang , Xuehan Xiong , Jianchao Yang
Abstract: Systems, devices, media, and methods are presented for modeling facial representations using image segmentation with a client device. The systems and methods receive an image depicting a face, detect at least a portion of the face within the image, and identify a set of facial features within the portion of the face. The systems and methods generate a descriptor function representing the set of facial features, fit object functions of the descriptor function, identify an identification probability for each facial feature, and assign an identification to each facial feature.
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公开(公告)号：US12169765B2
公开(公告)日：2024-12-17
申请号：US18244016
申请日：2023-09-08
Applicant: Snap Inc.
Inventor： Xuehan Xiong , Zehao Xue
Abstract: A machine learning scheme can be trained on a set of labeled training images of a subject in different poses, with different textures, and with different background environments. The label or marker data of the subject may be stored as metadata to a 3D model of the subject or rendered images of the subject. The machine learning scheme may be implemented as a supervised learning scheme that can automatically identify the labeled data to create a classification model. The classification model can classify a depicted subject in many different environments and arrangements (e.g., poses).
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公开(公告)号：US12159215B2
公开(公告)日：2024-12-03
申请号：US18489730
申请日：2023-10-18
Applicant: Snap Inc.
Inventor： Linjie Yang , Jianchao Yang , Xuehan Xiong , Yanran Wang
Abstract: A modulated segmentation system can use a modulator network to emphasize spatial prior data of an object to track the object across multiple images. The modulated segmentation system can use a segmentation network that receives spatial prior data as intermediate data that improves segmentation accuracy. The segmentation network can further receive visual guide information from a visual guide network to increase tracking accuracy via segmentation.
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Patent Agency Ranking
公开(公告)号：US20230362331A1
公开(公告)日：2023-11-09
申请号：US18221702
申请日：2023-07-13
Applicant: Snap Inc.
Inventor： Lidiia Bogdanovych , William Brendel , Samuel Edward Hare , Fedir Poliakov , Guohui Wang , Xuehan Xiong , Jianchao Yang , Linjie Yang
IPC: H04N7/14 , G06T7/11 , G06T7/194 , G06N3/08 , G06N3/04 , G06V30/242 , G06V10/82 , G06F18/214 , G06F18/24 , G06V30/19
CPC classification number: H04N7/147 , G06T7/11 , G06T7/194 , G06N3/08 , G06N3/04 , G06V30/242 , G06V10/82 , G06F18/214 , G06F18/24765 , G06V30/19173 , H04N7/141 , G06T2207/10024 , G06T2207/10016 , G06T2207/20024 , G06T2207/20221 , G06T2207/30201 , G06T2207/20081 , G06T2207/20084 , H04N5/44504
Abstract: A machine learning system can generate an image mask (e.g., a pixel mask) comprising pixel assignments for pixels. The pixels can be assigned to classes, including, for example, face, clothes, body skin, or hair. The machine learning system can be implemented using a convolutional neural network that is configured to execute efficiently on computing devices having limited resources, such as mobile phones. The pixel mask can be used to more accurately display video effects interacting with a user or subject depicted in the image.
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公开(公告)号：US11790276B2
公开(公告)日：2023-10-17
申请号：US17322609
申请日：2021-05-17
Applicant: Snap Inc.
Inventor： Xuehan Xiong , Zehao Xue
CPC classification number: G06N20/10 , G06N20/00 , G06T17/20 , G06V10/772 , G06V20/10 , G06V20/80 , G06V40/103 , G06V40/107
Abstract: A machine learning scheme can be trained on a set of labeled training images of a subject in different poses, with different textures, and with different background environments. The label or marker data of the subject may be stored as metadata to a 3D model of the subject or rendered images of the subject. The machine learning scheme may be implemented as a supervised learning scheme that can automatically identify the labeled data to create a classification model. The classification model can classify a depicted subject in many different environments and arrangements (e.g., poses).
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公开(公告)号：US20230274543A1
公开(公告)日：2023-08-31
申请号：US18312479
申请日：2023-05-04
Applicant: Snap Inc.
Inventor： Samuel Edward Hare , Fedir Poliakov , Guohui Wang , Xuehan Xiong , Jianchao Yang , Linjie Yang , Shah Tanmay Anilkumar
CPC classification number: G06V20/40 , G06T7/248 , G06V20/46 , G06T1/20 , G06T2207/20081 , G06T2200/28 , G06T2207/10016
Abstract: A mobile device can generate real-time complex visual image effects using asynchronous processing pipeline. A first pipeline applies a complex image process, such as a neural network, to keyframes of a live image sequence. A second pipeline generates flow maps that describe feature transformations in the image sequence. The flow maps can be used to process non-keyframes on the fly. The processed keyframes and non-keyframes can be used to display a complex visual effect on the mobile device in real-time or near real-time.
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公开(公告)号：US10929673B2
公开(公告)日：2021-02-23
申请号：US16654898
申请日：2019-10-16
Applicant: Snap Inc.
Inventor： Samuel Edward Hare , Fedir Poliakov , Guohui Wang , Xuehan Xiong , Jianchao Yang , Linjie Yang , Shah Tanmay Anilkumar
Abstract: A mobile device can generate real-time complex visual image effects using asynchronous processing pipeline. A first pipeline applies a complex image process, such as a neural network, to keyframes of a live image sequence. A second pipeline generates flow maps that describe feature transformations in the image sequence. The flow maps can be used to process non-keyframes on the fly. The processed keyframes and non-keyframes can be used to display a complex visual effect on the mobile device in real-time or near real-time.
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公开(公告)号：US20210027100A1
公开(公告)日：2021-01-28
申请号：US16992968
申请日：2020-08-13
Applicant: Snap Inc.
Inventor： Lidiia Bogdanovych , William Brendel , Samuel Edward Hare , Fedir Poliakov , Guohui Wang , Xuehan Xiong , Jianchao Yang , Linjie Yang
Abstract: A machine learning system can generate an image mask (e.g., a pixel mask) comprising pixel assignments for pixels. The pixels can he assigned to classes, including, for example, face, clothes, body skin, or hair. The machine learning system can be implemented. using a convolutional neural network that is configured to execute efficiently on computing devices having limited resources, such as mobile phones. The pixel mask can be used to more accurately display video effects interacting with a user or subject depicted in the image.
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