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    OBJECT DETECTION
    3.
    发明申请
    OBJECT DETECTION 有权

    公开(公告)号：US20230115167A1

    公开(公告)日：2023-04-13

    申请号：US17902025

    申请日：2022-09-02

    Applicant: HUAWEI TECHNOLOGIES CO., LTD.

    Inventor： Carlo BIFFI ,  Steven George MCDONAGH ,  Ales LEONARDIS ,  Sarah PARISOT

    IPC: G06V10/764 ,  G06V10/771 ,  G06N20/20

    Abstract: A device for categorising regions in images is disclosed. The device comprising: an input for receiving a first set of images, and defining one or more regions of for each image of the first set of images and a categorisation for the one or more regions, and a second set of images, and a categorisation for each image of the second set; and a processor configured to train a first machine learning algorithm to categorise features in images by: processing the images of the first and second set using the first algorithm to estimate feature regions in the images and a categorisation for each of the feature regions, and training the first algorithm in dependence on the categorisations received for the images of the first and second sets.

    RAW TO RGB IMAGE TRANSFORMATION
    4.
    发明申请
    RAW TO RGB IMAGE TRANSFORMATION 有权

    公开(公告)号：US20220247889A1

    公开(公告)日：2022-08-04

    申请号：US17721425

    申请日：2022-04-15

    Applicant: HUAWEI TECHNOLOGIES CO., LTD.

    Inventor： Francesca BABILONI ,  Ioannis MARRAS ,  Ales LEONARDIS ,  Gregory SLABAUGH

    IPC: H04N1/64 ,  G06T3/40

    Abstract: An image processor comprising a plurality of processing modules configured to transform a raw image into an output image, the modules comprising a first module and a second module, each of which implements a respective trained artificial intelligence model, wherein: the first module is configured to implement an image transformation operation that recovers luminance from the raw image; and the second module is configured to implement an image transformation operation that recovers chrominance from the raw image.

    FEATURE DETECTOR AND DESCRIPTOR
    5.
    发明申请
    FEATURE DETECTOR AND DESCRIPTOR 有权

    公开(公告)号：US20220245922A1

    公开(公告)日：2022-08-04

    申请号：US17726684

    申请日：2022-04-22

    Applicant: HUAWEI TECHNOLOGIES CO., LTD.

    Inventor： Axel BARROSO LAGUNA ,  Yannick VERDIE ,  Benjamin BUSAM ,  Ales LEONARDIS ,  Gregory SLABAUGH

    IPC: G06V10/44 ,  G06V10/82 ,  G06V10/25 ,  G06V10/774

    Abstract: The technology of this application related to an image processor comprising a plurality of modules, the plurality of modules comprising a first module and a second module, wherein the image processor is configured to receive an input image and output a plurality of mathematical descriptors for characteristic regions of the input image. The first module is configured to implement a first trained artificial intelligence model to detect a set of characteristic regions in the input image; and the second module is configured to implement a second trained artificial intelligence model to determine a mathematical descriptor for each of said set of characteristic regions. The first and second trained artificial intelligence models are collectively trained end to end.

    DOMAIN ADAPTATION FOR DEPTH DENSIFICATION
    6.
    发明申请
    DOMAIN ADAPTATION FOR DEPTH DENSIFICATION 有权

    公开(公告)号：US20220245841A1

    公开(公告)日：2022-08-04

    申请号：US17726668

    申请日：2022-04-22

    Applicant: HUAWEI TECHNOLOGIES CO., LTD.

    Inventor： Adrian LOPEZ RODRIGUEZ ,  Benjamin BUSAM ,  Gregory SLABAUGH ,  Ales LEONARDIS

    IPC: G06T7/50 ,  G06N20/00

    Abstract: A method for training an environmental analysis system, the method comprising: receiving a data model of an environment; forming, in dependence on the data model, a first training input comprising a visual stream representing the environment as viewed from a plurality of locations; forming, in dependence on the data model, a second training input comprising a depth stream representing depths of objects in the environment relative to the plurality of locations; forming a third training input, the third training input being sparser than the second training input; and estimating, using the analysis system, in dependence on the first and third training inputs, a series of depths at less sparsity than the third training input; and adapting the analysis system in dependence on a comparison between the estimated series of depths and the second training input.

    TIME-OF-FLIGHT DEPTH ENHANCEMENT
    7.
    发明申请
    TIME-OF-FLIGHT DEPTH ENHANCEMENT 有权

    公开(公告)号：US20220222839A1

    公开(公告)日：2022-07-14

    申请号：US17586034

    申请日：2022-01-27

    Applicant: HUAWEI TECHNOLOGIES CO., LTD.

    Inventor： Benjamin BUSAM ,  Patrick RUHKAMP ,  Matthieu HOG ,  Yannick VERDIE ,  Ales LEONARDIS ,  Gregory SLABAUGH

    IPC: G06T7/514

    Abstract: An image processing system configured to receive an input time-of-flight depth map representing the distance of objects in an image from a camera at a plurality of locations of pixels in the respective image, and in dependence on that map to generate an improved time-of-flight depth map for the image, the input time-of-flight depth map having been generated from at least one correlation image representing the overlap between emitted and reflected light signals at the plurality of locations of pixels at a given phase shift, the system being configured to generate the improved time-of-flight depth map from the input time-of-flight depth map in dependence on a colour representation of the respective image and at least one correlation image.

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