System and Methods for Photo In-painting of Unwanted Objects with Auxiliary Photos on Smartphone

    公开(公告)号:US20230306564A1

    公开(公告)日:2023-09-28

    申请号:US18328574

    申请日:2023-06-02

    CPC classification number: G06T5/005 G06T5/50 G06T2207/20212

    Abstract: A method and network device for correcting photos implemented by an image-capturing device, where the method includes: capturing a primary photo of a target, wherein the primary photo contains an unwanted object; capturing multiple auxiliary photos of a background region behind the target after capturing the primary photo; generating a first transformed auxiliary photo by mapping a first auxiliary photo to the primary photo, wherein the first auxiliary photo is selected from the multiple auxiliary photos; merging the first transformed auxiliary photo with the primary photo to generate a first merged photo in which the unwanted object is partially removed; and in-painting all or part of the unwanted object when the unwanted object is not completely removed from the first merged photo.

    Feature Data Encoding and Decoding Method and Apparatus

    公开(公告)号:US20240105193A1

    公开(公告)日:2024-03-28

    申请号:US18526406

    申请日:2023-12-01

    CPC classification number: G10L19/08

    Abstract: This application provides picture or audio encoding and decoding methods and apparatuses, and relates to the field of artificial intelligence (AI)—based picture or audio encoding and decoding technologies, and specifically, to the field of neural network-based picture feature map or audio feature variable encoding and decoding technologies. The encoding method includes: obtaining a to-be-encoded target, where the to-be-encoded target includes a plurality of feature elements, and the plurality of feature elements include a first feature element. The method further includes: obtaining a probability estimation result of the first feature element; determining, based on the probability estimation result of the first feature element, whether to perform entropy encoding on the first feature element; and performing entropy encoding on the first feature element only when it is determined that entropy encoding needs to be performed on the first feature element.

    Massively Scalable, Resilient, and Adaptive Federated Learning System

    公开(公告)号:US20230162047A1

    公开(公告)日:2023-05-25

    申请号:US18159571

    申请日:2023-01-25

    CPC classification number: G06N3/098

    Abstract: A federated learning system is disclosed. The system includes scalable queues configured to receive model update contributions from a plurality of clients. The model update contributions contain updated model parameters. The system also includes a model repository configured to store a model for access by a plurality of clients and receive the model with updates based on the updated model parameters. The system also includes a configuration repository configured to store model polices including an update threshold indicating how many responses need to be received from the plurality of clients to initiate an update of the model. The system also includes hierarchical aggregators configured to update the model based on the updated model parameters from the plurality of clients and based on the update threshold.

    SYSTEMS AND METHODS FOR RETRIEVING VIDEOS USING NATURAL LANGUAGE DESCRIPTION

    公开(公告)号:US20230086735A1

    公开(公告)日:2023-03-23

    申请号:US18071523

    申请日:2022-11-29

    Inventor: Ning Yan

    Abstract: Implementations are directed to methods, systems, and computer-readable media for obtaining videos and extracting, from each video, a key frame for the video including a timestamp. For each key frame, a scene graph is generated. Generating the scene graph for the key frame includes identifying, objects in the image, and extracting a relationship feature defining a relationship between a first object and a second, different object of the objects in the key frame. The scene graph for the key frame is generated that includes a set of nodes and a set of edges. A natural language query request for a video is received, including terms defining a relationship between two or more particular objects. A query graph is generated for the natural language query request, and a set of videos corresponding to the set of scene graphs matching the query graph are provided for display on a user device.

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