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    Adversarial learning for finegrained image search
    82.
    发明授权
    Adversarial learning for finegrained image search 有权

    公开(公告)号：US11361191B2

    公开(公告)日：2022-06-14

    申请号：US15985818

    申请日：2018-05-22

    Applicant: eBay Inc.

    Inventor： Kevin Lin ,  Fan Yang ,  Qiaosong Wang ,  Robinson Piramuthu

    IPC: G06K9/62 ,  G06F16/51 ,  G06F16/532 ,  G06F16/56 ,  G06N3/08 ,  G06V20/00 ,  G06F16/583 ,  G06V10/32

    Abstract: Disclosed are systems, methods, and non-transitory computer-readable media for using adversarial learning for fine-grained image search. An image search system receives a search query that includes an input image depicting an object. The search system generates, using a generator, a vector representation of the object in a normalized view. The generator was trained based on a set of reference images of known objects in multiple views, and feedback data received from an evaluator that indicates performance of the generator at generating vector representations of the known objects in the normalized view. The evaluator including a discriminator sub-module, a normalizer sub-module, and a semantic embedding sub-module that generate the feedback data. The image search system identifies, based on the vector representation of the object, a set of other images depicting the object, and returns at least one of the other images in response to the search query.

    CORRELATING IMAGE ANNOTATIONS WITH FOREGROUND FEATURES
    84.
    发明申请
    CORRELATING IMAGE ANNOTATIONS WITH FOREGROUND FEATURES 有权

    公开(公告)号：US20210182333A1

    公开(公告)日：2021-06-17

    申请号：US17107483

    申请日：2020-11-30

    Applicant: eBay Inc.

    Inventor： Anurag Bhardwaj ,  Robinson Piramuthu ,  Vicente Ordonez-Roman ,  Vignesh Jagadeesh ,  Wei Di

    IPC: G06F16/58 ,  G06F16/583 ,  G06K9/46 ,  G06F16/53 ,  G06F16/50 ,  G06T7/11 ,  G06T7/10 ,  G06F16/532

    Abstract: A machine may be configured to execute a machine-learning process for identifying and understanding fine properties of various items of various types by using images and associated corresponding annotations, such as titles, captions, tags, keywords, or other textual information applied to these images. By use of a machine-learning process, the machine may perform property identification accurately and without human intervention. These item properties may be used as annotations for other images that have similar features. Accordingly, the machine may answer user-submitted questions, such as “What do rustic items look like?,” and items or images depicting items that are deemed to be rustic can be readily identified, classified, ranked, or any suitable combination thereof.

    INTEGRATION OF 3D MODELS
    89.
    发明申请
    INTEGRATION OF 3D MODELS 审中-公开

    公开(公告)号：US20200234489A1

    公开(公告)日：2020-07-23

    申请号：US16776547

    申请日：2020-01-30

    Applicant: eBay Inc.

    Inventor： Qiaosong Wang ,  James Thomas Dowdell ,  Jinrong Xie ,  Robinson Piramuthu

    IPC: G06T15/20 ,  G06T17/20 ,  G06T7/90

    Abstract: In various example embodiments, a system and method for integration of a three-dimensional model is disclosed. In one example embodiment, a method includes receiving a plurality of images, selecting points on the images and triangulating the points to generate a plurality of depth maps, generate a three-dimensional mesh by combining the plurality of depth maps, generating a three-dimensional model of the item by projecting the plurality of images onto the mesh using the points, calibrating colors used in the model using colors diffuse properties of the colors in the images, and providing a user interface allowing a user to select one or more user points on the three-dimensional model and provide additional information associated with the selected user points.

    Generating a digital image using a generative adversarial network
    90.
    发明授权
    Generating a digital image using a generative adversarial network 有权

    公开(公告)号：US10552714B2

    公开(公告)日：2020-02-04

    申请号：US15923347

    申请日：2018-03-16

    Applicant: eBay Inc.

    Inventor： Mohammadhadi Kiapour ,  Shuai Zheng ,  Robinson Piramuthu ,  Omid Poursaeed

    IPC: G06K9/00 ,  G06K9/66 ,  G06K9/62 ,  G06K9/32 ,  G06Q30/06 ,  G06F16/532 ,  G06F16/583 ,  G06F16/9535

    Abstract: Various embodiments described herein utilize multiple levels of generative adversarial networks (GANs) to facilitate generation of digital images based on user-provided images. Some embodiments comprise a first generative adversarial network (GAN) and a second GAN coupled to the first GAN, where the first GAN includes an image generator and at least two discriminators, and the second GAN includes an image generator and at least one discriminator. According to some embodiments, the (first) image generator of the first GAN is trained by processing a user-provided image using the first GAN. For some embodiments, the user-provided image and the first generated image, generated by processing the user-provided image using the first GAN, are combined to produce a combined image. For some embodiments, the (second) image generator of the second GAN is trained by processing the combined image using the second GAN.

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