AVATAR GENERATION BASED ON DRIVING VIEWS
    242.
    发明公开

    公开(公告)号:US20240096041A1

    公开(公告)日:2024-03-21

    申请号:US17932645

    申请日:2022-09-15

    Abstract: Systems and methods are provided that include a processor executing an avatar generation program to obtain driving view(s), calculate a skeletal pose of the user, and generate a coarse human mesh based on a template mesh and the skeletal pose of the user. The program further constructs a texture map based on the driving view(s) and the coarse human mesh, extracts a plurality of image features from the texture map, the image features being aligned to a UV map, and constructs a UV positional map based on the coarse human mesh. The program further extracts a plurality of pose features from the UV positional map, the pose features being aligned to the UV map, generates a plurality of pose-image features based on the UV map-aligned image features and UV map-aligned pose features, and renders an avatar based on the plurality of pose-image features.

    ACCELERATING DATA PROCESSING BY OFFLOADING THREAD COMPUTATION

    公开(公告)号:US20240095076A1

    公开(公告)日:2024-03-21

    申请号:US17945843

    申请日:2022-09-15

    CPC classification number: G06F9/5027 G06F9/4843

    Abstract: The present disclosure describes techniques for accelerating data processing by offloading thread computation. An application may be started based on creating and executing a process by a host, the process associated with a plurality of threads. Creating a plurality of computation threads on a storage device may be requested based on determining that the storage device represents a computational storage. The plurality of computation threads may be created based on preloading a plurality of libraries in the storage device. The plurality of libraries may comprise executable codes associated with the plurality of threads. Data processing associated with the plurality of threads may be offloaded to the storage device using the plurality of computation threads. Activities associated with the plurality of computation threads may be managed by the process.

    Methods and systems for motion candidate derivation

    公开(公告)号:US11936899B2

    公开(公告)日:2024-03-19

    申请号:US17200631

    申请日:2021-03-12

    Applicant: Lemon Inc.

    Abstract: Embodiments of the present disclosure provide methods, apparatuses and computer storage media for video processing. One example method comprises determining, during a conversion between a current video block of a video and a bitstream of the video, at least one set of motion candidates for the current video block, each motion candidate comprising predicted motion information determined from neighboring video blocks of the current video block; determining, based on a template of the current video block and from the at least one set of motion candidates, a target motion candidate for the current video block by using a template matching cost rule; and performing the conversion based on the target motion candidate.

    METHOD, APPARATUS, DEVICE AND STORAGE MEDIUM FOR RECOMMENDING INFORMATION

    公开(公告)号:US20240086685A1

    公开(公告)日:2024-03-14

    申请号:US18463389

    申请日:2023-09-08

    CPC classification number: G06N3/0464

    Abstract: A method, apparatus, device and storage medium for recommending information. The method includes determining, based on a set of feature representations of a plurality of features associated with information recommendation, a first set of weights indicating importance of the plurality of features. The method also includes determining a second set of weights based on the set of feature representations and the first set of weights. The method further includes recommending the information to a user based on the set of feature representations, the first set of weights and the second set of weights. The importance of respective features associated with the information recommendation can be accurately determined through this method, which further improves the effectiveness of information recommendation and improves the user experience.

    UNLEARNING OF RECOMMENDATION MODELS
    249.
    发明公开

    公开(公告)号:US20240070525A1

    公开(公告)日:2024-02-29

    申请号:US17897697

    申请日:2022-08-29

    Applicant: Lemon Inc.

    CPC classification number: G06N20/00 G06F21/6245

    Abstract: The present disclosure describes techniques of performing machine unlearning in a recommendation model. An unlearning process of the recommendation model may be initiated in response to receiving a request for deleting a fraction of user data from any particular user. The recommendation model may be pre-trained to recommend content to users based at least in part on user data. Values of entries in a matrix corresponding to the fraction of user data may be configured as zero. The matrix may comprise entries denoting preferences of users with respect to content items. Confidence values associated with the fraction of user data may be configured as zero to block influence of the fraction of user data on performance of the recommendation model. The unlearning process may be implemented by performing a number of iterations until the recommendation model has converged.

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