公开(公告)号：US11857045B2

公开(公告)日：2024-01-02

申请号：US17581183

申请日：2022-01-21

Applicant: Snap Inc.

Inventor： Stephen Andrew Steger ,  Tiffany Ming Tsao ,  Qiaokun Huang

IPC: H02J7/00 ,  H02J7/14 ,  A45C11/04 ,  H02J7/34

CPC classification number: A45C11/04 ,  H02J7/0044 ,  H02J7/0047 ,  H02J7/342 ,  H02J7/0048

Abstract: A carry case for an electronics-enabled eyewear device has incorporated therein electronic components for connection to the eyewear device while storing the eyewear device. The case comprises a rigid frame structure defining an openable holding space for the pair of smart glasses, and a compressible shock-resistant protective cover on the frame structure. The exterior of the case may be predominantly defined by the shock resistant protective cover.

公开(公告)号：US20230419530A1

公开(公告)日：2023-12-28

申请号：US17852134

申请日：2022-06-28

Applicant: Snap Inc.

Inventor： Pawel Wawruch

IPC: G06T7/70 ,  G06T19/00 ,  G06T19/20

CPC classification number: G06T7/70 ,  G06T19/006 ,  G06T19/20

Abstract: An image copying assistant is a computing application configured to aid users in copying a digital image to a physical canvas using traditional media on the physical canvas. The image copying assistant utilizes augmented reality techniques to present features of the digital image projected onto the physical canvas. The image copying assistant detects previously generated markers in an output of a digital image sensor of a camera of a computing device and use the detected markers to calculate the plane and boundaries of the surface of the physical canvas. The image copying assistant uses the calculated plane and boundaries to determine a position of the digital image on a display of the computing device.

公开(公告)号：US20230418976A1

公开(公告)日：2023-12-28

申请号：US18244797

申请日：2023-09-11

Applicant: Snap Inc.

Inventor： Vasyl Pihur ,  Subhash Sankuratripati ,  Dachuan Huang ,  Leah Fortier

IPC: G06F21/62

CPC classification number: G06F21/6245

Abstract: Methods and systems for identifying personally identifiable information (PII) are disclosed. In some aspects, frequency maps of fields storing known PII information are generated. The frequency maps may count occurrences of unique bigrams in the PII fields. A field of interest may then be analyzed to generate a second frequency map. Correlations between the first frequency maps and the second frequency map may be generated. If one of the correlations meets certain criterion, the disclosed embodiments may determine that the field of interest does or does not include PII. Access control for the field of interest may then be based on whether the field includes PII. In some aspects, a storage location of data included in the field of interest may be based on whether the field includes PII.

公开(公告)号：US20230418385A1

公开(公告)日：2023-12-28

申请号：US17851465

申请日：2022-06-28

Applicant: Snap Inc.

Inventor： Alex Feinman ,  Ashwani Arya

IPC: G06F3/01 ,  G01S13/08

CPC classification number: G06F3/017 ,  G06F3/011 ,  G01S13/08

Abstract: A method for a low-power hand-tracking system is described. In one aspect, a method includes polling a proximity sensor of a wearable device to detect a proximity event, the wearable device includes a low-power processor and a high-power processor, in response to detecting the proximity event, operating a low-power hand-tracking application on the low-power processor based on proximity data from the proximity sensor, and ending an operation of the low-power hand-tracking application in response to at least one of: detecting and recognizing a gesture based on the proximity data, detecting without recognizing the gesture based on the proximity data, or detecting a lack of activity from the proximity sensor within a timeout period based on the proximity data.

公开(公告)号：US11855938B2

公开(公告)日：2023-12-26

申请号：US17400643

申请日：2021-08-12

Applicant: Snap Inc.

Inventor： John Jensen ,  Swetha Krishna Prabhakar

IPC: H04L51/046 ,  H04L67/306 ,  G06Q30/0242 ,  A63F13/87 ,  G06Q30/0273 ,  G06Q20/38 ,  G06Q20/36 ,  G06Q30/0207

CPC classification number: H04L51/046 ,  A63F13/87 ,  G06Q20/363 ,  G06Q20/367 ,  G06Q20/381 ,  G06Q30/0207 ,  G06Q30/0246 ,  G06Q30/0274 ,  H04L67/306

Abstract: Aspects of the present disclosure involve a system and a method for performing operations comprising: receiving, by a messaging application, content from a given user; selecting a metric for measuring performance of the content on the messaging application; measuring performance of the content on the messaging application; computing a value of the performance of the content on the messaging application based on the selected metric; and updating a restricted use token wallet stored in a profile for the given user based on the computed value of the performance of the content.

公开(公告)号：US11853399B2

公开(公告)日：2023-12-26

申请号：US18059928

申请日：2022-11-29

Applicant: Snap Inc.

Inventor： Jianfei Yu ,  Luis Carlos Dos Santos Marujo ,  Venkata Satya Pradeep Karuturi ,  Leonardo Ribas Machado das Neves ,  Ning Xu ,  William Brendel

IPC: G06F40/30 ,  G06F18/2431 ,  G06N3/08 ,  G06N20/20 ,  G06F40/284 ,  G06N3/045 ,  G10L25/30 ,  G06F40/295 ,  G06F40/279 ,  G06F40/289 ,  G10L15/18 ,  G10L15/06

CPC classification number: G06F18/2431 ,  G06F40/284 ,  G06F40/30 ,  G06N3/045 ,  G06N3/08 ,  G06N20/20 ,  G06F40/279 ,  G06F40/289 ,  G06F40/295 ,  G10L15/06 ,  G10L15/1807 ,  G10L15/1815 ,  G10L15/1822 ,  G10L25/30

Abstract: Sentiment classification can be implemented by an entity-level multimodal sentiment classification neural network. The neural network can include left, right, and target entity subnetworks. The neural network can further include an image network that generates representation data that is combined and weighted with data output by the left, right, and target entity subnetworks to output a sentiment classification for an entity included in a network post.

公开(公告)号：US20230412896A1

公开(公告)日：2023-12-21

申请号：US18240484

申请日：2023-08-31

Applicant: Snap Inc.

Inventor： David Michael Hornsby ,  Jeffrey Kile ,  Chinmay Lonkar ,  Zhimin Wang ,  Ian Anthony Wehrman ,  Khalil Chatoo

IPC: H04N21/81 ,  H04N21/845 ,  H04N21/234 ,  H04L51/046 ,  H04L51/10

CPC classification number: H04N21/812 ,  H04N21/8456 ,  H04N21/23424 ,  H04L51/046 ,  H04L51/10

Abstract: Aspects of the present disclosure involve a system comprising a computer-readable storage medium storing a program and method for inserting ads into a video. The program and method provide for receiving a request to play a video, the video comprising plural shots separated by breakpoints, each shot of the plural shots corresponding to a contiguous sequence of video frames that is free of cuts or transitions; initiating, in response to receiving the request, playback of the video from a selected shot of the plural shots; receiving indication of an ad to present at a breakpoint following the selected shot; determining, in response to receiving the indication, that a first threshold amount of time has passed since initiating the playback of the video; and inserting, based on the determining, the ad at the breakpoint following the selected shot.

公开(公告)号：US20230410479A1

公开(公告)日：2023-12-21

申请号：US17841333

申请日：2022-06-15

Applicant: Snap Inc.

Inventor： Sergey Demyanov ,  Konstantin Gudkov ,  Fedor Zhdanov ,  Andrei Zharkov

IPC: G06V10/774 ,  G06V10/82 ,  G06V10/74 ,  G06V40/16 ,  G06T3/00 ,  G06T11/00 ,  G06T7/68

CPC classification number: G06V10/774 ,  G06V10/82 ,  G06V10/74 ,  G06V40/16 ,  G06T3/0093 ,  G06T11/00 ,  G06T7/68 ,  G06T2207/20081 ,  G06T2207/20084 ,  G06T2207/30201 ,  G06T2207/20221

Abstract: An image manipulation system for generating modified images using a generative adversarial network (GAN) trains GANs using domain changes, aligns input images with generated images, classifies and associates target images based on a symmetry, and uses a modified discriminator structure. A method for domain changes includes generating, using a pre-trained GAN trained on a plurality of first target images, a plurality of images, and determining a feature for each of the plurality of images. The method further includes determining the feature for each of a plurality of second target images and matching, based on the feature, second target images of the plurality of second target images with the plurality of images. The method further includes training a discriminator of the pre-trained GAN with the second target images and the plurality of images.

公开(公告)号：US20230410450A1

公开(公告)日：2023-12-21

申请号：US18240380

申请日：2023-08-31

Applicant: Snap Inc.

Inventor： Kyle Goodrich ,  Samuel Edward Hare ,  Maxim Maximov Lazarov ,  Tony Mathew ,  Andrew James McPhee ,  Daniel Moreno ,  Dhritiman Sagar ,  Wentao Shang

IPC: G06T19/20 ,  G06N20/00 ,  G06F3/04842 ,  G06F3/04883 ,  G06T15/50 ,  G06T7/507 ,  G06V40/16

CPC classification number: G06T19/20 ,  G06N20/00 ,  G06F3/04842 ,  G06F3/04883 ,  G06T15/50 ,  G06T7/507 ,  G06V40/171 ,  G06T2219/2012 ,  G06T2219/2024

Abstract: The subject technology applies, to image data and depth data, a 3D effect including at least one beautification operation based on an augmented reality content generator, the 3D effect including a beautification operation, the beautification operation comprising modifying image data, the image data including a region corresponding to a representation of a face, the beautification operation comprising using a machine learning model for at least one of smoothing blemishes or preserving facial skin texture. The subject technology generates a depth map using at least the depth data. The subject technology generates a segmentation mask based at least on the image data. The subject technology performs background inpainting and blurring of the image data using at least the segmentation mask to generate background inpainted image data. The subject technology generates a 3D message based at least in part on the applied 3D effect including the at least one beautification operation.

公开(公告)号：US20230410442A1

公开(公告)日：2023-12-21

申请号：US18240373

申请日：2023-08-31

Applicant: Snap Inc.

Inventor： Kyle Goodrich ,  Samuel Edward Hare ,  Maxim Maximov Lazarov ,  Tony Mathew ,  Andrew James McPhee ,  Daniel Moreno ,  Wentao Shang

IPC: G06T19/00 ,  G06F3/0482 ,  G06F3/0488 ,  G06T5/00 ,  G06F3/04815

CPC classification number: G06T19/006 ,  G06F3/0482 ,  G06F3/0488 ,  G06T5/005 ,  G06F3/04815 ,  G06T2207/10028

Abstract: The subject technology generates a segmentation mask based on first image data. The subject technology applies the segmentation mask on first depth data to reduce a set of artifacts in a depth map based on the first depth data. The subject technology generates a packed depth map based at least in part on the depth map. The subject technology converts a single channel floating point texture to a raw depth map. The subject technology generates multiple channels. The subject technology applies, to the first image data and the first depth data, a first augmented reality content generator corresponding to a selected first selectable graphical item, the first image data and the first depth data being captured with a camera. The subject technology generates a message including the applied first augmented reality content generator to the first image data and the first depth data.