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    Distractor classifier
    5.
    发明授权
    Distractor classifier 有权

    公开(公告)号：US11462040B2

    公开(公告)日：2022-10-04

    申请号：US17082479

    申请日：2020-10-28

    Applicant: ADOBE INC.

    Inventor： Zhe Lin ,  Luis Figueroa ,  Zhihong Ding ,  Scott Cohen

    IPC: G06V40/10 ,  G06N3/08 ,  G06K9/62 ,  G06T3/40 ,  G06V10/50

    Abstract: A distractor detector includes a heatmap network and a distractor classifier. The heatmap network operates on an input image to generate a heatmap for a main subject, a heatmap for a distractor, and optionally a heatmap for the background. Each object is cropped within the input image to generate a corresponding cropped image. Regions within the heatmaps that correspond to the objects are identified, and each of the regions is cropped within each of the heatmaps to generate cropped heatmaps. The distractor classifier then operates on the cropped images and the cropped heatmaps to classify each of the objects as being either a main subject or a distractor.

    DILATING OBJECT MASKS TO REDUCE ARTIFACTS DURING INPAINTING
    7.
    发明公开
    DILATING OBJECT MASKS TO REDUCE ARTIFACTS DURING INPAINTING 审中-公开

    公开(公告)号：US20240169501A1

    公开(公告)日：2024-05-23

    申请号：US18058601

    申请日：2022-11-23

    Applicant: Adobe Inc.

    Inventor： Qing Liu ,  Zhe Lin ,  Luis Figueroa ,  Scott Cohen

    IPC: G06T5/00 ,  G06T7/11 ,  G06T7/194

    CPC classification number: G06T5/005 ,  G06T5/002 ,  G06T7/11 ,  G06T7/194 ,  G06T2200/24 ,  G06T2207/20084

    Abstract: The present disclosure relates to systems, methods, and non-transitory computer-readable media that modify digital images via scene-based editing using image understanding facilitated by artificial intelligence. For instance, in one or more embodiments, the disclosed systems generate, utilizing a segmentation neural network and without user input, object masks for objects in a digital image. The disclosed systems determine foreground and background abutting an object mask. The disclosed systems generate an expanded object mask by expanding the object mask into the foreground abutting the object mask by a first amount and expanding the object mask into the background abutting the object mask by a second amount that differs from the first amount. The disclosed systems inpaint a hole corresponding to the expanded object mask utilizing an inpainting neural network.

    REMOVING DISTRACTING OBJECTS FROM DIGITAL IMAGES
    8.
    发明公开
    REMOVING DISTRACTING OBJECTS FROM DIGITAL IMAGES 审中-公开

    公开(公告)号：US20240171848A1

    公开(公告)日：2024-05-23

    申请号：US18058554

    申请日：2022-11-23

    Applicant: Adobe Inc.

    Inventor： Luis Figueroa ,  Zhihong Ding ,  Scott Cohen ,  Zhe Lin ,  Qing Liu

    IPC: H04N23/63 ,  G06V10/26 ,  G06V10/764 ,  G06V10/82 ,  G06V10/94 ,  H04N5/262

    CPC classification number: H04N23/632 ,  G06V10/273 ,  G06V10/764 ,  G06V10/82 ,  G06V10/945 ,  H04N5/2628

    Abstract: The present disclosure relates to systems, methods, and non-transitory computer-readable media that modify digital images via scene-based editing using image understanding facilitated by artificial intelligence. For instance, in one or more embodiments, the disclosed systems provide, for display within a graphical user interface of a client device, a digital image displaying a plurality of objects, the plurality of objects comprising a plurality of different types of objects. The disclosed systems generate, utilizing a segmentation neural network and without user input, an object mask for objects of the plurality of objects. The disclosed systems determine, utilizing a distractor detection neural network, a classification for the objects of the plurality of objects. The disclosed systems remove at least one object from the digital image, based on classifying the at least one object as a distracting object, by deleting the object mask for the at least one object.

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