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公开(公告)号：US09275078B2
公开(公告)日：2016-03-01
申请号：US14288233
申请日：2014-05-27
Applicant: eBay Inc.
Inventor： Anurag Bhardwaj , Mohammad Haris Baig , Robinson Piramuthu , Vignesh Jagadeesh , Wei Di
IPC: G06F17/30
CPC classification number: G06T7/50 , G06F17/3025 , G06F17/30256 , G06F17/30262 , G06F17/30277 , G06K9/00208 , G06K9/4609 , G06T7/194 , G06T7/62 , G06T2207/10024 , G06T2207/10028 , G06T2207/20081
Abstract: During a training phase, a machine accesses reference images with corresponding depth information. The machine calculates visual descriptors and corresponding depth descriptors from this information. The machine then generates a mapping that correlates these visual descriptors with their corresponding depth descriptors. After the training phase, the machine may perform depth estimation based on a single query image devoid of depth information. The machine may calculate one or more visual descriptors from the single query image and obtain a corresponding depth descriptor for each visual descriptor from the generated mapping. Based on obtained depth descriptors, the machine creates depth information that corresponds to the submitted single query image.
Abstract translation: 在训练阶段，机器访问具有相应深度信息的参考图像。 该机器根据该信息计算视觉描述符和相应的深度描述符。 然后，机器生成将这些可视描述符与其相应的深度描述符相关联的映射。 在训练阶段之后，机器可以基于没有深度信息的单个查询图像来执行深度估计。 机器可以从单个查询图像计算一个或多个可视描述符，并从所生成的映射中获得每个可视描述符的相应深度描述符。 基于获得的深度描述符，机器创建与提交的单个查询图像相对应的深度信息。
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公开(公告)号：US09245191B2
公开(公告)日：2016-01-26
申请号：US14479217
申请日：2014-09-05
Applicant: eBay, Inc.
Inventor： Anurag Bhardwaj , Chen-Yu Lee , Robinson Piramuthu , Vignesh Jagadeesh , Wei Di
CPC classification number: G06K9/18 , G06K9/3258 , G06K9/6231 , G06K9/6267 , G06K2009/4666 , G06T11/60
Abstract: Apparatus and method for performing accurate text recognition of non-simplistic images (e.g., images with clutter backgrounds, lighting variations, font variations, non-standard perspectives, and the like) may employ a machine-learning approach to identify a discriminative feature set selected from among features computed for a plurality of irregularly positioned, sized, and/or shaped (e.g., randomly selected) image sub-regions.
Abstract translation: 用于执行非简单图像（例如，具有杂波背景的图像，照明变化，字体变化，非标准透视等）的精确文本识别的装置和方法可以采用机器学习方法来识别所选择的区分特征集 从针对多个不规则定位，尺寸和/或成形（例如，随机选择）的图像子区域计算的特征中。
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公开(公告)号：US11657084B2
公开(公告)日：2023-05-23
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 , G06F16/53 , G06F16/50 , G06T7/11 , G06T7/10 , G06F16/532 , G06V10/40 , G06V10/46
CPC classification number: G06F16/58 , G06F16/50 , G06F16/53 , G06F16/532 , G06F16/583 , G06F16/5838 , G06F16/5846 , G06F16/5854 , G06F16/5862 , G06T7/10 , G06T7/11 , G06V10/40 , G06V10/462
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.
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公开(公告)号：US11449719B2
公开(公告)日：2022-09-20
申请号：US16225338
申请日：2018-12-19
Applicant: eBay Inc.
Inventor： Wei Di , Vignesh Jagadeesh , Robinson Piramuthu , Elizabeth Churchill , Anurag Bhardwaj
IPC: G06K9/00 , G06K9/62 , G06F16/58 , G06F16/583 , G06V10/40 , G06Q30/06 , G06Q30/02 , G06F16/60 , G06F16/63
Abstract: A machine may be configured to perform image evaluation of images depicting items for sale and to provide recommendations for improving the images depicting the items to increase the sales of the items depicted in the images. For example, the machine accesses a result of a user behavior analysis. The machine receives an image of an item from a user device. The machine performs an image evaluation of the received image based on an analysis of the received image and the result of the user behavior analysis. The performing of the image evaluation may include determining a likelihood of a user engaging in a desired user behavior in relation to the received image. Then, the machine generates, based on the evaluation of the received image, an output that references the received image and indicates the likelihood of a user engaging in the desired behavior.
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公开(公告)号：US11120478B2
公开(公告)日：2021-09-14
申请号：US14963026
申请日：2015-12-08
Applicant: eBay Inc.
Inventor： Kota Hara , Vignesh Jagadeesh , Robinson Piramuthu
Abstract: For an input image of a person, a set of object proposals are generated in the form of bounding boxes. A pose detector identifies coordinates in the image corresponding to locations on the person's body, such as the waist, head, hands, and feet of the person. A convolutional neural network receives the portions of the input image defined by the bounding boxes and generates a feature vector for each image portion. The feature vectors are input to one or more support vector machine classifiers, which generate an output representing a probability of a match with an item. The distance between the bounding box and a joint associated with the item is used to modify the probability. The modified probabilities for the support vector machine are then compared with a threshold and each other to identify the item.
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Patent Agency Ranking
公开(公告)号：US10282642B2
公开(公告)日：2019-05-07
申请号：US15788115
申请日：2017-10-19
Applicant: eBay Inc.
Inventor： Mohammadhadi Kiapour , Wei Di , Vignesh Jagadeesh , Robinson Piramuthu
Abstract: An image is passed through an image identifier to identify a coarse category for the image and a bounding box for a categorized object. A mask is used to identify the portion of the image that represents the object. Given the foreground mask, the convex hull of the mask is located and an aligned rectangle of minimum area that encloses the hull is fitted. The aligned bounding box is rotated and scaled, so that the foreground object is roughly moved to a standard orientation and size (referred to as calibrated). The calibrated image is used as an input to a fine-grained categorization module, which determines the fine category within the coarse category for the input image.
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公开(公告)号：US09858492B2
公开(公告)日：2018-01-02
申请号：US14971143
申请日：2015-12-16
Applicant: eBay Inc.
Inventor： Anurag Bhardwaj , Chen-Yu Lee , Robinson Piramuthu , Vignesh Jagadeesh , Wei Di
CPC classification number: G06K9/18 , G06K9/3258 , G06K9/6231 , G06K9/6267 , G06K2009/4666 , G06T11/60
Abstract: Apparatus and method for performing accurate text recognition of non-simplistic images (e.g., images with clutter backgrounds, lighting variations, font variations, non-standard perspectives, and the like) may employ a machine-learning approach to identify a discriminative feature set selected from among features computed for a plurality of irregularly positioned, sized, and/or shaped (e.g., randomly selected) image sub-regions.
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公开(公告)号：US20170323185A1
公开(公告)日：2017-11-09
申请号：US15661722
申请日：2017-07-27
Applicant: eBay Inc.
Inventor： Anurag Bhardwaj , Wei Di , Vignesh Jagadeesh , Robinson Piramuthu , Neelakantan Neelakantan
CPC classification number: G06K9/66 , G06F16/24578 , G06F16/532 , G06F16/583 , G06F16/5838 , G06F16/5866 , G06F16/9535 , G06K9/4642 , G06K9/4647 , G06K9/4652 , G06K9/6215 , G06K9/6217 , G06Q30/0629 , G06Q30/0631 , G06Q30/0643 , G06T7/13 , G06T7/41 , G06T7/90 , G06T2207/10024
Abstract: An apparatus and method to facilitate providing recommendations are disclosed herein. A query image is received via a user interface. An image attribute from the query image is extracted. A determination that a usage condition for an image index is satisfied by the query image based on a comparison of an image attribute of the image index to the image attribute of the query image is performed. In response to the determination that the usage condition for the image index is satisfied by the query image, the image index is selected. Based on the selected image index and the usage condition, a set of item images from a plurality of item images stored in a database that correspond to the selected image index is identified. The identified set of item images are presented at the user interface.
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公开(公告)号：US09721192B2
公开(公告)日：2017-08-01
申请号：US15065122
申请日：2016-03-09
Applicant: eBay Inc.
Inventor： Anurag Bhardwaj , Wei Di , Vignesh Jagadeesh , Robinson Piramuthu , Neelakantan Sundaresan
CPC classification number: G06K9/66 , G06F17/30247 , G06F17/3025 , G06F17/30256 , G06F17/30268 , G06F17/30277 , G06F17/3053 , G06F17/30867 , G06K9/4642 , G06K9/4647 , G06K9/4652 , G06K9/6215 , G06K9/6217 , G06Q30/0629 , G06Q30/0631 , G06Q30/0643 , G06T7/13 , G06T7/41 , G06T7/90 , G06T2207/10024
Abstract: An apparatus and method to facilitate finding complementary recommendations are disclosed herein. One or more fashion trend or pleasing color combination rules are determined based on data obtained from one or more sources. One or more template images and rule triggers corresponding to the fashion trend or pleasing color combination rules are generated, each of the rule triggers associated with at least one of the template images. A processor compares a first image attribute of a particular one of the template images to a second image attribute of each of a plurality of inventory images corresponding to the plurality of inventory items to identify the inventory items complementary to the query image. The particular one of the template images is selected based on the rule trigger corresponding to the particular one of the template images being applicable for a query image.
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公开(公告)号：US09594774B2
公开(公告)日：2017-03-14
申请号：US14994459
申请日：2016-01-13
Applicant: eBay Inc.
Inventor： Anurag Bhardwaj , Mohammad Haris Baig , Robinson Piramuthu , Vignesh Jagadeesh , Wei Di
CPC classification number: G06T7/50 , G06F17/3025 , G06F17/30256 , G06F17/30262 , G06F17/30277 , G06K9/00208 , G06K9/4609 , G06T7/194 , G06T7/62 , G06T2207/10024 , G06T2207/10028 , G06T2207/20081
Abstract: During a training phase, a machine accesses reference images with corresponding depth information. The machine calculates visual descriptors and corresponding depth descriptors from this information. The machine then generates a mapping that correlates these visual descriptors with their corresponding depth descriptors. After the training phase, the machine may perform depth estimation based on a single query image devoid of depth information. The machine may calculate one or more visual descriptors from the single query image and obtain a corresponding depth descriptor for each visual descriptor from the generated mapping. Based on obtained depth descriptors, the machine creates depth information that corresponds to the submitted single query image.
Abstract translation: 在训练阶段，机器访问具有相应深度信息的参考图像。 该机器根据该信息计算视觉描述符和相应的深度描述符。 然后，机器生成将这些可视描述符与其相应的深度描述符相关联的映射。 在训练阶段之后，机器可以基于没有深度信息的单个查询图像来执行深度估计。 机器可以从单个查询图像计算一个或多个可视描述符，并从所生成的映射中获得每个可视描述符的相应深度描述符。 基于获得的深度描述符，机器创建与提交的单个查询图像相对应的深度信息。
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