Virtual dressing room
    1.
    发明授权

    公开(公告)号:US10346893B1

    公开(公告)日:2019-07-09

    申请号:US15076332

    申请日:2016-03-21

    Applicant: A9.com, Inc.

    Abstract: Machine learning-based approaches are used to identify complementary sets of items, such as articles of clothing and accessories that “match,” and suggest items that would complement a given item of interest. A simulated representation of how the item of interest and the identified complementary items would look together is then generated. For example, given a particular piece of clothing or other apparel item of interest, additional items that complement the item of interest can be identified and suggested to a potential purchaser of the item. Additionally, a three-dimensional (3D) or pseudo-3D representation of a human body can be generated to model the apparel item of interest and the identified complementary apparel items to give the user an idea of how the suggested outfit would look on a user. The representation can be modified to more closely resemble a particular user.

    Image similarity-based group browsing

    公开(公告)号:US11423076B2

    公开(公告)日:2022-08-23

    申请号:US16378230

    申请日:2019-04-08

    Applicant: A9.com, Inc.

    Abstract: Various approaches discussed herein enable browsing groups of visually similar items to an item of interest, wherein the item of interest may be identified in a query image, for example. One or more visual attributes associated with the item of interest are identified, and the visually similar items matching at least one of the visual attributes are grouped together, wherein the group is ranked according to the visually similar items' overall visual similarity to the item of interest, for example by using a visual similarity score and/or metric.

    Image similarity-based group browsing

    公开(公告)号:US10282431B1

    公开(公告)日:2019-05-07

    申请号:US14974388

    申请日:2015-12-18

    Applicant: A9.com, Inc.

    Abstract: Various approaches discussed herein enable browsing groups of visually similar items to an item of interest, wherein the item of interest may be identified in a query image, for example. One ore more visual attributes associated with the item of interest are identified, and the visually similar items matching at least one of the visual attributes are grouped together, wherein the group is ranked according to the visually similar items' overall visual similarity to the item of interest, for example by using a visual similarity score and/or metric.

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