Fashion preference analysis
    6.
    发明授权

    公开(公告)号:US11599929B2

    公开(公告)日:2023-03-07

    申请号:US17102194

    申请日:2020-11-23

    Applicant: eBay Inc.

    Abstract: A machine is configured to determine fashion preferences of users and to provide item recommendations based on the fashion preferences. For example, the machine accesses an indication of a fashion style of a user. The fashion style is determined based on automatically captured data pertaining to the user. The machine identifies, based on the fashion style, one or more fashion items from an inventory of fashion items. The machine generates one or more selectable user interface elements for inclusion in a user interface. The one or more user interface elements correspond to the one or more fashion items. The machine causes generation and display of the user interface that includes the one or more selectable user interface elements. A selection of a selectable user interface element results in display of a combination of an image of a particular fashion item and an image of an item worn by the user.

    Searchable texture index
    8.
    发明授权

    公开(公告)号:US11494823B2

    公开(公告)日:2022-11-08

    申请号:US17154520

    申请日:2021-01-21

    Applicant: eBay Inc.

    Abstract: Electronic content that has a tactile dimension when presented on a tactile-enabled computing device may be referred to as tactile-enabled content. A tactile-enabled device is a device that is capable of presenting tactile-enabled content in a manner that permits a user to experience tactile quality of electronic content. In one example embodiment, a system is provided for generating content that has a tactile dimension when presented on a tactile-enabled device.

    ADVERSARIAL LEARNING FOR FINEGRAINED IMAGE SEARCH

    公开(公告)号:US20220245406A1

    公开(公告)日:2022-08-04

    申请号:US17727100

    申请日:2022-04-22

    Applicant: eBay Inc.

    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.

    GENERATING A DIGITAL IMAGE USING A GENERATIVE ADVERSARIAL NETWORK

    公开(公告)号:US20220092367A1

    公开(公告)日:2022-03-24

    申请号:US17539558

    申请日:2021-12-01

    Applicant: eBay Inc.

    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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