CONTENT NAVIGATION WITH AUTOMATED CURATION

    公开(公告)号:US20230063920A1

    公开(公告)日:2023-03-02

    申请号:US18049098

    申请日:2022-10-24

    Applicant: Snap Inc.

    Abstract: Systems, devices, methods, media, and instructions for automated image processing and content curation are described. In one embodiment a server computer system communicates at least a portion of a first content collection to a first client device, and receives a first selection communication in response, the first selection communication identifying a first piece of content of the first plurality of pieces of content. The server analyzes analyzing the first piece of content to identify a set of context values for the first piece of content, and accesses accessing a second content collection comprising pieces of content sharing at least a portion of the set of context values of the first piece of content. In various embodiments, different content values, image processing operations, and content selection operations are used to curate the content collections.

    DENSE FEATURE SCALE DETECTION FOR IMAGE MATCHING

    公开(公告)号:US20220292697A1

    公开(公告)日:2022-09-15

    申请号:US17825994

    申请日:2022-05-26

    Applicant: Snap Inc.

    Abstract: Dense feature scale detection can be implemented using multiple convolutional neural networks trained on scale data to more accurately and efficiently match pixels between images. An input image can be used to generate multiple scaled images. The multiple scaled images are input into a feature net, which outputs feature data for the multiple scaled images. An attention net is used to generate an attention map from the input image. The attention map assigns emphasis as a soft distribution to different scales based on texture analysis. The feature data and the attention data can be combined through a multiplication process and then summed to generate dense features for comparison.

    IMAGE AND POINT CLOUD BASED TRACKING AND IN AUGMENTED REALITY SYSTEMS

    公开(公告)号:US20210174578A1

    公开(公告)日:2021-06-10

    申请号:US17248833

    申请日:2021-02-10

    Applicant: Snap Inc.

    Abstract: Systems and methods for image based location estimation are described. In one example embodiment, a first positioning system is used to generate a first position estimate. Point cloud data describing an environment is then accessed. A two-dimensional surface of an image of an environment is captured, and a portion of the image is matched to a portion of key points in the point cloud data. An augmented reality object is then aligned within one or more images of the environment based on the match of the point cloud with the image. In some embodiments, building façade data may additionally be used to determine a device location and place the augmented reality object within an image.

    DENSE CAPTIONING WITH JOINT INTERFERENCE AND VISUAL CONTEXT

    公开(公告)号:US20200320353A1

    公开(公告)日:2020-10-08

    申请号:US16946346

    申请日:2020-06-17

    Applicant: Snap Inc.

    Abstract: A dense captioning system and method is provided for analyzing an image to generate proposed bounding regions for a plurality of visual concepts within the image, generating a region feature for each proposed bounding region to generate a plurality of region features of the image, and determining a context feature for the image using a proposed bounding region that is a largest in size of the proposed bounding regions. For each region feature of the plurality of region features of the image, the dense captioning system and method further provides for analyzing the region feature to determine for the region feature a detection score that indicates a likelihood that the region feature comprises an actual object, and generating a caption for a visual concept in the image using the region feature and the context feature when a detection score is above a specified threshold value.

    PROCESSING AND FORMATTING VIDEO FOR INTERACTIVE PRESENTATION

    公开(公告)号:US20200152238A1

    公开(公告)日:2020-05-14

    申请号:US16743563

    申请日:2020-01-15

    Applicant: Snap Inc.

    Abstract: Systems and methods are described for determining a first media item related to an event, of a plurality of stored media items each comprising video content related to the event, that was captured in a device orientation corresponding to a first device orientation detected for the first computing device; providing, to the first computing device, the first media item to be displayed on the first computing device; in response to a detected change to a second device orientation for the first computing device, determining a second media item that was captured in a device orientation corresponding to the second device orientation detected for the first computing device; and providing, to the first computing device, the second media item to be displayed on the first computing device.

    Dense feature scale detection for image matching

    公开(公告)号:US10552968B1

    公开(公告)日:2020-02-04

    申请号:US15712990

    申请日:2017-09-22

    Applicant: Snap Inc.

    Abstract: Dense feature scale detection can be implemented using multiple convolutional neural networks trained on scale data to more accurately and efficiently match pixels between images. An input image can be used to generate multiple scaled images. The multiple scaled images are input into a feature net, which outputs feature data for the multiple scaled images. An attention net is used to generate an attention map from the input image. The attention map assigns emphasis as a soft distribution to different scales based on texture analysis. The feature data and the attention data can be combined through a multiplication process and then summed to generate dense features for comparison.

    NEURAL NETWORKS FOR FACIAL MODELING
    10.
    发明申请

    公开(公告)号:US20190332852A1

    公开(公告)日:2019-10-31

    申请号:US16509083

    申请日:2019-07-11

    Applicant: Snap Inc.

    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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