Machine Learning Techniques for Differentiability Scoring of Digital Images

    公开(公告)号:US20220083809A1

    公开(公告)日:2022-03-17

    申请号:US17021279

    申请日:2020-09-15

    Applicant: Adobe Inc.

    Abstract: An image differentiation system receives input feature vectors for multiple input images and reference feature vectors for multiple reference images. In some cases, the feature vectors are extracted by an image feature extraction module trained based on training image triplets. A differentiability scoring module determines a differentiability score for each input image based on a distance between the input feature vectors and the reference feature vectors. The distance for each reference feature vector is modified by a weighting factor based on interaction metrics associated with the corresponding reference image. In some cases, an input image is identified as a differentiated image based on the corresponding differentiability score. Additionally or alternatively, an image modification module determines an image modification that increases the differentiability score of the input image. The image modification module generates a recommended image by applying the image modification to the input image.

    ACCESSIBLE AND EFFICIENT SEARCH PROCESS USING CLUSTERING

    公开(公告)号:US20210216540A1

    公开(公告)日:2021-07-15

    申请号:US16739678

    申请日:2020-01-10

    Applicant: Adobe Inc.

    Abstract: Techniques are disclosed for narrowing search requests, based on interaction between a search system and a user. For example, a plurality of search results is generated in response to a search query. To reduce the number of search results, a plurality of attributes or features of the search results are identified. Each feature has a corresponding plurality of clusters, where a cluster of a feature represents a corresponding range or value of the feature. For each feature, the first plurality of search results is categorized into the corresponding plurality of clusters of the corresponding feature. A feature is then selected. The search system interacts with the user, to identify a cluster of the plurality of clusters of the selected feature in which one or more intended search results belong. Based on such identification of the cluster, the search system refines or narrows down the first plurality of search results.

    Visually augmenting images of three-dimensional containers with virtual elements

    公开(公告)号:US11836850B2

    公开(公告)日:2023-12-05

    申请号:US17336109

    申请日:2021-06-01

    Applicant: Adobe Inc.

    CPC classification number: G06T15/50 G06T7/40 G06T7/50 G06T19/20

    Abstract: Certain embodiments involve visually augmenting images of three-dimensional containers with virtual elements that fill one or more empty regions of the three-dimensional containers. For instance, a computing system receives a first image that depicts a storage container and identify sub-containers within the storage container. The computing system selects, from a virtual object library, a plurality of virtual objects that are semantically related to the sub-container. The computing system determines an arrangement of the virtual objects within the sub-container based on semantics associated with the sub-container and the plurality of virtual objects. The computing system generates a second image that depicts the arrangement of the plurality of virtual objects within the storage container and sub-containers. The computing system generates, for display, the second image depicting the storage container and the arrangement of the virtual objects.

    VISUALLY AUGMENTING IMAGES OF THREE-DIMENSIONAL CONTAINERS WITH VIRTUAL ELEMENTS

    公开(公告)号:US20210287425A1

    公开(公告)日:2021-09-16

    申请号:US17336109

    申请日:2021-06-01

    Applicant: Adobe Inc.

    Abstract: Certain embodiments involve visually augmenting images of three-dimensional containers with virtual elements that fill one or more empty regions of the three-dimensional containers. For instance, a computing system receives a first image that depicts a storage container and identify sub-containers within the storage container. The computing system selects, from a virtual object library, a plurality of virtual objects that are semantically related to the sub-container. The computing system determines an arrangement of the virtual objects within the sub-container based on semantics associated with the sub-container and the plurality of virtual objects. The computing system generates a second image that depicts the arrangement of the plurality of virtual objects within the storage container and sub-containers. The computing system generates, for display, the second image depicting the storage container and the arrangement of the virtual objects.

    Visually augmenting images of three-dimensional containers with virtual elements

    公开(公告)号:US11055905B2

    公开(公告)日:2021-07-06

    申请号:US16535780

    申请日:2019-08-08

    Applicant: Adobe Inc.

    Abstract: Certain embodiments involve visually augmenting images of three-dimensional containers with virtual elements that fill one or more empty regions of the three-dimensional containers. For instance, a computing system receives a first image that depicts a storage container and identify sub-containers within the storage container. The computing system selects, from a virtual object library, a plurality of virtual objects that are semantically related to the sub-container. The computing system determines an arrangement of the virtual objects within the sub-container based on semantics associated with the sub-container and the plurality of virtual objects. The computing system generates a second image that depicts the arrangement of the plurality of virtual objects within the storage container and sub-containers. The computing system generates, for display, the second image depicting the storage container and the arrangement of the virtual objects.

    Image shadow detection using multiple images

    公开(公告)号:US10997453B2

    公开(公告)日:2021-05-04

    申请号:US16260762

    申请日:2019-01-29

    Applicant: Adobe Inc.

    Abstract: While a user holds a camera positioned relative to an object, a first image of the object and a second image of the object, as captured by the camera, may be obtained. Intensity variations between a first intensity map of the first image and a combination intensity map obtained from the first intensity map and a second intensity map of the second image may be compared. Then, a shadow may be identified within the first image, based on the intensity variations.

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