Interactive silent liveness detection

    公开(公告)号:US11922732B2

    公开(公告)日:2024-03-05

    申请号:US17551554

    申请日:2021-12-15

    Applicant: PayPal, Inc.

    CPC classification number: G06V40/45 G06V10/24 G06V10/60 G06V40/161

    Abstract: A liveness detection system uses a combination of interactive and silent tests to verify physical presence of a live person at a client device. The system superimposes a box on a live video of the space in front of the client device and instructs the user to move to a position that places his or her face within the box. While the user's face is within the box, the system captures a sequence of frames from the video while an amount of illumination cast on the user's face is switched between bright and dark levels according to a random, semi-random, or predefined flash sequence. The system analyzes the resulting sequence of frames to confirm that the user's head pose is consistent with the location of the box, and that changes in brightness of the image of the user's face across the captured frames are consistent with the flash sequence.

    IMAGE FORGERY DETECTION VIA HEADPOSE ESTIMATION

    公开(公告)号:US20220318597A1

    公开(公告)日:2022-10-06

    申请号:US17236085

    申请日:2021-04-21

    Applicant: PayPal, Inc.

    Abstract: Systems and/or techniques for facilitating image forgery detection via headpose estimation are provided. In various embodiments, a system can receive a document from a client device. In various cases, the system can identify, by executing a first trained machine learning model, an object that is depicted in the document. In various instances, the system can determine, by executing a second trained machine learning model, a pose of the object. In various aspects, the system can determine, by executing a third trained machine learning model, whether the document is authentic or forged based on the pose of the object. In various embodiments, the system can, in response to determining that the document is forged, transmit an unsuccessful validation message to the client device.

    AUTOMATIC DOCUMENT PROCESSING
    6.
    发明申请

    公开(公告)号:US20210350516A1

    公开(公告)日:2021-11-11

    申请号:US16870627

    申请日:2020-05-08

    Applicant: PayPal, Inc.

    Abstract: Techniques are disclosed relating to determining whether document objects included in an image correspond to known document types. In some embodiments, a computing system maintains information specifying a set of known document types. In some embodiments, the computing system receives an image that includes objects. In some embodiments, the computing system analyzes, using a first neural network, the image to identify a document object and location information specifying a location of the document object within the image. In some embodiments, the computing system determines, using a second neural network, whether the document object within the image corresponds to a document type specified in the set of known document types, where the determining is performed based on the location information of the document object. In some embodiments, disclosed techniques may assist in automatically extracting information from documents, which in turn may advantageously decrease processing time for onboarding new customers.

    Two-sided machine learning framework for pointer movement-based bot detection

    公开(公告)号:US12216745B2

    公开(公告)日:2025-02-04

    申请号:US18146738

    申请日:2022-12-27

    Applicant: PAYPAL, INC.

    Abstract: Methods and systems are presented for bot detection. A movement of a pointing device is tracked via a graphical user interface (GUI) of an application executable at a user device. Movement data associated with different locations of the pointing device within the GUI is obtained. The movement data is mapped to functional areas corresponding to a range of the different locations of the pointing device within the GUI over consecutive time intervals. At least one vector representing a sequence of movements for at least one trajectory of the pointing device through one or more of the functional areas and a duration the pointing device stays within each functional area is generated. At least one trained machine learning model is used to determine whether the sequence of movements of the pointing device was produced through human interaction with the pointing device by an actual user of the user device.

    Systems and methods for formatting informal utterances

    公开(公告)号:US12198685B2

    公开(公告)日:2025-01-14

    申请号:US18184432

    申请日:2023-03-15

    Applicant: PAYPAL, INC.

    Abstract: Methods and systems are presented for translating informal utterances into formal texts. Informal utterances may include words in abbreviation forms or typographical errors. The informal utterances may be processed by mapping each word in an utterance into a well-defined token. The mapping from the words to the tokens may be based on a context associated with the utterance derived by analyzing the utterance in a character-by-character basis. The token that is mapped for each word can be one of a vocabulary token that corresponds to a formal word in a pre-defined word corpus, an unknown token that corresponds to an unknown word, or a masked token. Formal text may then be generated based on the mapped tokens. Through the processing of informal utterances using the techniques disclosed herein, the informal utterances are both normalized and sanitized.

    SYSTEMS AND METHODS FOR FORMATTING INFORMAL UTTERANCES

    公开(公告)号:US20230290344A1

    公开(公告)日:2023-09-14

    申请号:US18184432

    申请日:2023-03-15

    Applicant: PAYPAL, INC.

    CPC classification number: G06F40/284 G06F40/205

    Abstract: Methods and systems are presented for translating informal utterances into formal texts. Informal utterances may include words in abbreviation forms or typographical errors. The informal utterances may be processed by mapping each word in an utterance into a well-defined token. The mapping from the words to the tokens may be based on a context associated with the utterance derived by analyzing the utterance in a character-by-character basis. The token that is mapped for each word can be one of a vocabulary token that corresponds to a formal word in a pre-defined word corpus, an unknown token that corresponds to an unknown word, or a masked token. Formal text may then be generated based on the mapped tokens. Through the processing of informal utterances using the techniques disclosed herein, the informal utterances are both normalized and sanitized.

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