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    Digital content query-aware sequential search
    221.
    发明授权
    Digital content query-aware sequential search 有权

    公开(公告)号：US12124439B2

    公开(公告)日：2024-10-22

    申请号：US17513127

    申请日：2021-10-28

    Applicant: Adobe Inc.

    Inventor： Handong Zhao ,  Zhe Lin ,  Zhaowen Wang ,  Zhankui He ,  Ajinkya Gorakhnath Kale

    IPC: G06F16/245 ,  G06F16/248 ,  G06N20/00

    CPC classification number: G06F16/245 ,  G06F16/248 ,  G06N20/00

    Abstract: Digital content search techniques are described that overcome the challenges found in conventional sequence-based techniques through use of a query-aware sequential search. In one example, a search query is received and sequence input data is obtained based on the search query. The sequence input data describes a sequence of digital content and respective search queries. Embedding data is generated based on the sequence input data using an embedding module of a machine-learning model. The embedding module includes a query-aware embedding layer that generates embeddings of the sequence of digital content and respective search queries. A search result is generated referencing at least one item of digital content by processing the embedding data using at least one layer of the machine-learning model.

    Locally constrained self-attentive sequential recommendation
    223.
    发明授权
    Locally constrained self-attentive sequential recommendation 有权

    公开(公告)号：US12019671B2

    公开(公告)日：2024-06-25

    申请号：US17501191

    申请日：2021-10-14

    Applicant: Adobe Inc.

    Inventor： Handong Zhao ,  Zhankui He ,  Zhaowen Wang ,  Ajinkya Gorakhnath Kale ,  Zhe Lin

    IPC: G06F16/43 ,  G06F16/438 ,  G06F16/44 ,  G06N3/045

    CPC classification number: G06F16/438 ,  G06F16/447 ,  G06N3/045

    Abstract: Digital content search techniques are described. In one example, the techniques are incorporated as part of a multi-head self-attention module of a transformer using machine learning. A localized self-attention module, for instance, is incorporated as part of the multi-head self-attention module that applies local constraints to the sequence. This is performable in a variety of ways. In a first instance, a model-based local encoder is used, examples of which include a fixed-depth recurrent neural network (RNN) and a convolutional network. In a second instance, a masking-based local encoder is used, examples of which include use of a fixed window, Gaussian initialization, and an adaptive predictor.

    PANOPTICALLY GUIDED INPAINTING UTILIZING A PANOPTIC INPAINTING NEURAL NETWORK
    228.
    发明公开
    PANOPTICALLY GUIDED INPAINTING UTILIZING A PANOPTIC INPAINTING NEURAL NETWORK 审中-公开

    公开(公告)号：US20240127410A1

    公开(公告)日：2024-04-18

    申请号：US17937695

    申请日：2022-10-03

    Applicant: Adobe Inc.

    Inventor： Zhe Lin ,  Haitian Zheng ,  Elya Shechtman ,  Jianming Zhang ,  Jingwan Lu ,  Ning Xu ,  Qing Liu ,  Scott Cohen ,  Sohrab Amirghodsi

    IPC: G06T5/00 ,  G06T7/11

    CPC classification number: G06T5/005 ,  G06T7/11 ,  G06T2207/20084

    Abstract: The present disclosure relates to systems, methods, and non-transitory computer readable media for panoptically guiding digital image inpainting utilizing a panoptic inpainting neural network. In some embodiments, the disclosed systems utilize a panoptic inpainting neural network to generate an inpainted digital image according to panoptic segmentation map that defines pixel regions corresponding to different panoptic labels. In some cases, the disclosed systems train a neural network utilizing a semantic discriminator that facilitates generation of digital images that are realistic while also conforming to a semantic segmentation. The disclosed systems generate and provide a panoptic inpainting interface to facilitate user interaction for inpainting digital images. In certain embodiments, the disclosed systems iteratively update an inpainted digital image based on changes to a panoptic segmentation map.

    Generating refined segmentations masks via meticulous object segmentation
    230.
    发明授权
    Generating refined segmentations masks via meticulous object segmentation 有权

    公开(公告)号：US11875510B2

    公开(公告)日：2024-01-16

    申请号：US17200525

    申请日：2021-03-12

    Applicant: Adobe Inc.

    Inventor： Yilin Wang ,  Chenglin Yang ,  Jianming Zhang ,  He Zhang ,  Zhe Lin

    IPC: G06K9/00 ,  G06T7/11 ,  G06N3/08 ,  G06T3/40 ,  G06F18/213 ,  G06N3/044

    CPC classification number: G06T7/11 ,  G06F18/213 ,  G06N3/044 ,  G06N3/08 ,  G06T3/4046 ,  G06T2207/20084

    Abstract: The present disclosure relates to systems, methods, and non-transitory computer-readable media that utilizes a neural network having a hierarchy of hierarchical point-wise refining blocks to generate refined segmentation masks for high-resolution digital visual media items. For example, in one or more embodiments, the disclosed systems utilize a segmentation refinement neural network having an encoder and a recursive decoder to generate the refined segmentation masks. The recursive decoder includes a deconvolution branch for generating feature maps and a refinement branch for generating and refining segmentation masks. In particular, in some cases, the refinement branch includes a hierarchy of hierarchical point-wise refining blocks that recursively refine a segmentation mask generated for a digital visual media item. In some cases, the disclosed systems utilize a segmentation refinement neural network that includes a low-resolution network and a high-resolution network, each including an encoder and a recursive decoder, to generate the refined segmentation masks.

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