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    TRAINING NEURAL NETWORKS
    25.
    发明公开
    TRAINING NEURAL NETWORKS 审中-公开

    公开(公告)号：US20230316729A1

    公开(公告)日：2023-10-05

    申请号：US17711951

    申请日：2022-04-01

    Applicant: DeepMind Technologies Limited

    Inventor： Dan-Andrei Calian ,  Sven Adrian Gowal ,  Timothy Arthur Mann ,  András György

    IPC: G06V10/774 ,  G06V10/82 ,  G06V10/776

    CPC classification number: G06V10/7747 ,  G06V10/82 ,  G06V10/776

    Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media for processing a network input using a trained neural network with network parameters to generate an output for a machine learning task. The training includes: receiving a set of training examples each including a training network input and a reference output; for each training iteration, generating a corrupted network input for each training network input using a corruption neural network; updating perturbation parameters of the corruption neural network using a first objective function based on the corrupted network inputs; generating an updated corrupted network input for each training network input based on the updated perturbation parameters; and generating a network output for each updated corrupted network input using the neural network; for each training example, updating the network parameters using a second objective function based on the network output and the reference output.

    Identity Preserved Controllable Facial Image Manipulation
    26.
    发明公开
    Identity Preserved Controllable Facial Image Manipulation 审中-公开

    公开(公告)号：US20230316591A1

    公开(公告)日：2023-10-05

    申请号：US17709895

    申请日：2022-03-31

    Applicant: Adobe Inc.

    Inventor： Zhixin Shu ,  Zhe Lin ,  Yuchen Liu ,  Yijun Li ,  Richard Zhang

    IPC: G06T11/00 ,  G06V10/40 ,  G06V10/774

    CPC classification number: G06T11/00 ,  G06V10/40 ,  G06V10/7747

    Abstract: Techniques for identity preserved controllable facial image manipulation are described that support generation of a manipulated digital image based on a facial image and a render image. For instance, a facial image depicting a facial representation of an individual is received as input. A feature space including an identity parameter and at least one other visual parameter is extracted from the facial image. An editing module edits one or more of the visual parameters and preserves the identity parameter. A renderer generates a render image depicting a morphable model reconstruction of the facial image based on the edit. The render image and facial image are encoded, and a generator of a neural network is implemented to generate a manipulated digital image based on the encoded facial image and the encoded render image.

    LEARNING BASED BAD PIXEL CORRECTION
    27.
    发明公开
    LEARNING BASED BAD PIXEL CORRECTION 审中-公开

    公开(公告)号：US20230316471A1

    公开(公告)日：2023-10-05

    申请号：US17657171

    申请日：2022-03-30

    Applicant: SAMSUNG ELECTRONICS CO., LTD.

    Inventor： Igal Avishai ,  Gal Bitan ,  Roy Yam

    IPC: G06T5/20 ,  G06V10/778 ,  H04N5/232 ,  G06V10/774 ,  G06V10/762 ,  G06T9/00 ,  G06V10/22

    CPC classification number: G06T5/20 ,  G06V10/778 ,  H04N5/23229 ,  G06T2207/20081 ,  G06V10/762 ,  G06T9/00 ,  G06V10/22 ,  G06V10/7747

    Abstract: Methods and apparatuses for correcting bad image pixels are described. The described sensor-independent image processing techniques leverage one or more dynamic dictionaries of learned filters for bad pixel correction (e.g., where a camera leverages such dictionaries to efficiently identify filters to accurately adjust and correct bad pixel values). For example, a dictionary may store filters that are learned offline (via a self-supervised learning algorithm implemented at a server using known images and ground truth bad pixel correction values). To select a filter for a bad pixel correction operation, a camera may encode an image patch surrounding a bad pixel (into an encoded patch descriptor) and search the dictionary for a matching patch descriptor key. The camera may then apply the filter (value) corresponding to the searched patch descriptor (key) of the dictionary to the image patch to correct the bad pixel and generate a corrected output image.

    GESTURE RECOGNITION ON RESOURCE-CONSTRAINED DEVICES
    28.
    发明公开
    GESTURE RECOGNITION ON RESOURCE-CONSTRAINED DEVICES 审中-公开

    公开(公告)号：US20230315209A1

    公开(公告)日：2023-10-05

    申请号：US17710888

    申请日：2022-03-31

    Applicant: SONY GROUP CORPORATION

    Inventor： KRISHNA PRASAD AGARA VENKATESHA RAO ,  SRINIDHI SRINIVASA ,  AKSHAY SHEKHAR KADAKOL

    IPC: G06F3/01 ,  G06V10/82 ,  G06V10/774 ,  H04L67/04

    CPC classification number: G06F3/017 ,  G06V10/82 ,  G06V10/7747 ,  H04L67/04

    Abstract: An electronic device for gesture recognition on resource-constrained devices is provided. The electronic device controls storage of a plurality of first consecutive image frames in a first buffer of a first length. The plurality of first consecutive image frames corresponds to the first length. The electronic device recognizes a first hand sign of a plurality of hand signs in a first subset of image frames of the plurality of first consecutive image frames. The electronic device controls storage of the recognized first hand sign in a second buffer of a second length based on the determination that a ratio of a number of the first subset of image frames and the first length is one of equal to or greater than the threshold. The electronic device determines a gesture corresponding to one or more hand signs of the plurality of hand signs stored in the second buffer.

    Image processing method and apparatus, electronic device and storage medium
    30.
    发明授权
    Image processing method and apparatus, electronic device and storage medium 有权

    公开(公告)号：US11756288B2

    公开(公告)日：2023-09-12

    申请号：US17569232

    申请日：2022-01-05

    Applicant: BAIDU USA LLC

    Inventor： Xinyang Zhang ,  Zhisheng Hu ,  Zhenyu Zhong

    IPC: G06K9/00 ,  G06V10/774 ,  G06T5/50

    CPC classification number: G06V10/7747 ,  G06T5/50 ,  G06T2207/10048 ,  G06T2207/20081 ,  G06T2207/20084 ,  G06T2207/20221

    Abstract: The present disclosure provides an image processing method and apparatus, an electronic device and a storage medium, which relate to the field of computer technology, and more particularly to artificial intelligence technology including computer vision, deep learning and the like. The image processing method includes: recognizing the image to be processed to determine attribute information of each object included in the image to be processed; determining a target thermal image to be recognized according to the attribute information of each object and the image to be processed; reconstructing the target thermal image to generate a first reconstructed image; and determining whether the image to be processed includes an object of a preset class according to a difference between the first reconstructed image and the target thermal image.

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