Weakly supervised semantic parsing
    33.
    发明授权

    公开(公告)号:US11727710B2

    公开(公告)日:2023-08-15

    申请号:US17508384

    申请日:2021-10-22

    Applicant: Snap Inc.

    CPC classification number: G06V40/107 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.

    SYSTEMS AND METHODS FOR DIGITAL IMAGE EDITING

    公开(公告)号:US20230004708A1

    公开(公告)日:2023-01-05

    申请号:US17811822

    申请日:2022-07-11

    Applicant: Snap Inc.

    Abstract: A system according to various exemplary embodiments includes a processor and a user interface, communication module, and memory coupled to the processor. The memory stores instructions that, when executed by the processor, cause the system to: retrieve a digital image from a server using the communication module; present the digital image on a display of the user interface; receive edits to the digital image via the user interface; generate, based on the edits, a modified digital image, wherein generating the modified digital image includes transforming a format of the digital image to include a field containing an identifier associated with the modified digital image; and transmit the modified digital image to the server using the communication module.

    Dense feature scale detection for image matching

    公开(公告)号:US11367205B1

    公开(公告)日:2022-06-21

    申请号:US16721483

    申请日:2019-12-19

    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.

    Efficient human pose tracking in videos

    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.

    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.

    Neural network-based image stream modification

    公开(公告)号:US11288879B2

    公开(公告)日:2022-03-29

    申请号:US15929374

    申请日:2020-04-29

    Applicant: Snap Inc.

    Abstract: Systems, devices, media, and methods are presented for object detection and inserting graphical elements into an image stream in response to detecting the object. The systems and methods detect an object of interest in received frames of a video stream. The systems and methods identify a bounding box for the object of interest and estimate a three-dimensional position of the object of interest based on a scale of the object of interest. The systems and methods generate one or more graphical elements having a size based on the scale of the object of interest and a position based on the three-dimensional position estimated for the object of interest. The one or more graphical elements are generated within the video stream to form a modified video stream. The systems and methods cause presentation of the modified video stream including the object of interest and the one or more graphical elements.

    SYSTEMS AND METHODS FOR DIGITAL IMAGE EDITING

    公开(公告)号:US20200342166A1

    公开(公告)日:2020-10-29

    申请号:US16946948

    申请日:2020-07-13

    Applicant: Snap Inc.

    Abstract: A system according to various exemplary embodiments includes a processor and a user interface, communication module, and memory coupled to the processor. The memory stores instructions that, when executed by the processor, cause the system to: retrieve a digital image from a server using the communication module; present the digital image on a display of the user interface; receive edits to the digital image via the user interface; generate, based on the edits, a modified digital image, wherein generating the modified digital image includes transforming a format of the digital image to include a field containing an identifier associated with the modified digital image; and transmit the modified digital image to the server using the communication module.

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