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公开(公告)号：US20200167981A1
公开(公告)日：2020-05-28
申请号：US16202979
申请日：2018-11-28
Applicant: Adobe Inc.
Inventor： Sanjeev Tagra , Sachin Soni , Prasenjit Mondal , Ajay Jain
Abstract: In implementations of jointly editing related objects in a digital image, an image editing application segments a first object in a digital image, and an additional object corresponding to the first object, such a shadow cast by the first object, a reflection of the first object, or an object of a same object class as the first object. Respective stick diagrams for the first object and the additional object are generated, and a mapping of the first object to the additional object is generated based on the stick diagrams. Based on a user request to edit the first object, such as to warp the first object, the first object and the additional object are jointly edited based on the mapping. Accordingly, realistic digital images are efficiently generated that maintain correspondence between related objects, without requiring a user to edit each object individually, thus saving time and resources.
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公开(公告)号：US20240428291A1
公开(公告)日：2024-12-26
申请号：US18213651
申请日：2023-06-23
Applicant: Adobe Inc.
Inventor： Ajay Jain , Eric Kienle
IPC: G06Q30/0251
Abstract: Systems and methods for predictively and dynamically updating content using nested A/B testing are provided. In certain embodiments, a system may assign a content item to a dynamic content portion of a communication. The communication may be sent to a first plurality of recipients. The system may receive information about interactions of a second plurality of recipients with the communication, wherein the second plurality of recipients is a subset of the first plurality of recipients. The system can determine a first conversion metric. The system can then compare the first conversion metric to a conversion metric threshold and based on the comparison, modify the dynamic content portion of the communication to generate a modified communication. The modified communication may be sent to a third plurality of recipients, wherein the third plurality of recipients is a subset of the first plurality of recipients not including the second plurality of recipients.
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公开(公告)号：US12124539B2
公开(公告)日：2024-10-22
申请号：US18213641
申请日：2023-06-23
Applicant: Adobe Inc.
Inventor： Arshiya Aggarwal , Sanjeev Tagra , Sachin Soni , Ryan Rozich , Prasenjit Mondal , Jonathan Roeder , Ajay Jain
IPC: G06F18/22 , G06F18/2113 , G06N5/04 , G06T5/50 , G06V10/40
CPC classification number: G06F18/22 , G06F18/2113 , G06N5/04 , G06T5/50 , G06V10/40 , G06T2207/20081 , G06T2207/20084
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.
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公开(公告)号：US20240320544A1
公开(公告)日：2024-09-26
申请号：US18187864
申请日：2023-03-22
Applicant: Adobe Inc.
Inventor： Ajay Jain , Michele Saad
Abstract: An object affinity determination and scoring system is described that is configured to support control by object providers in locating related objects. In a first example, an affinity system supports generation of affinity rules through interaction with a rule generation user interface. In a second example, the affinity system supports training and retraining of a machine-learning model to generate the affinity score. In a third example, the affinity scoring module supports output of a user interface having an input portion that supports user interaction to determine an affinity of selected objects to each other.
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公开(公告)号：US11727209B2
公开(公告)日：2023-08-15
申请号：US16859780
申请日：2020-04-27
Applicant: Adobe Inc.
Inventor： Ajay Jain , Sanjeev Tagra , Sachin Soni , Niranjan Shivanand Kumbi , Eric Andrew Kienle , Ajay Awatramani , Abhishek Jain
IPC: G06F40/279 , G06N3/08 , G06N3/044
CPC classification number: G06F40/279 , G06N3/044 , G06N3/08
Abstract: In implementations of systems for role classification, a computing device implements a role system to receive data describing a corpus of text that is associated with a user ID. Feature values of features are generated by a first machine learning model by processing the corpus of text, the features representing questions with respect to the corpus of text and the feature values representing answers to the questions included in the corpus of text. A classification of a role is generated by a second machine learning model by processing the feature values, the classification of the role indicating a relationship of the user ID with respect to a product or service. The role system outputs an indication of the classification of the role for display in a user interface of a display device.
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Patent Agency Ranking
公开(公告)号：US11482041B2
公开(公告)日：2022-10-25
申请号：US17076002
申请日：2020-10-21
Applicant: ADOBE INC.
Inventor： Sanjeev Tagra , Sachin Soni , Ajay Jain , Ryan Rozich , Jonathan Roeder , Arshiya Aggarwal , Prasenjit Mondal
Abstract: Methods, apparatus, and systems are provided for obfuscating facial identity in images by synthesizing a new facial image for an input image. A base face is detected from or selected for an input image. Facial images that are similar to the base face are selected and combined to create a new facial image. The new facial image is added to the input image such that the input image includes a combination of the base face and the new facial image. Where no base face is detected in the input image, a base face is selected from reference facial images based at least on pose keypoints identified in the input image. After a new facial image is generated based on the selected base face, a combination of the new facial image and the base facial image are added to the input image by aligning one or more pose keypoints.
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公开(公告)号：US11430030B1
公开(公告)日：2022-08-30
申请号：US17186495
申请日：2021-02-26
Applicant: Adobe Inc.
Inventor： Sanjeev Tagra , Sachin Soni , Ryan Rozich , Nitish Maurya , Jonathan Roeder , Ajay Jain , Ajay Bedi
Abstract: Techniques are disclosed for generating image recommendations to facilitate the sale of a product. An example methodology includes identifying a product category associated with an image of the product provided by the seller, and a product sub-category associated with the product image. The method further includes retrieving one or more images of for-sale items. The retrieval is based on a search of for-sale listings using the identified product category and the identified product sub-category. The method further includes clustering the retrieved images of for-sale items into groups, each group associated with a perspective viewpoint of the for-sale item. The method further includes providing a selected image from each group as an image recommendation. The selection is based on a value score associated with each of the images of the for-sale items. A graphical status indicating completeness of the seller's image set is updated in response to recommended images being adopted.
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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.
Inventor： Arshiya Aggarwal , Sanjeev Tagra , Sachin Soni , Ryan Rozich , Prasenjit Mondal , Jonathan Roeder , Ajay Jain
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.
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公开(公告)号：US11175807B1
公开(公告)日：2021-11-16
申请号：US17166495
申请日：2021-02-03
Applicant: Adobe Inc.
Inventor： Ajay Jain , Sanjeev Tagra , Sachin Soni , Eric Kienle
IPC: G06F3/0484 , G06F3/0481 , G06N5/04 , H04L12/58 , H04L29/08
Abstract: Techniques are provided for customizing, based on a user's activity over time, the selection of a video thumbnail for inclusion as a selectable interface element or element of a graphical interface. A server computer identifies events associated with prior interactions of a user and computes a time-decayed metric based on the time of a predicted future action of the user in comparison to a respective time of each identified event. Based on the time-decayed metric, the server computer selects a video thumbnail that is more relevant to the first event than the second event for presentation to the user.
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公开(公告)号：US20210303825A1
公开(公告)日：2021-09-30
申请号：US17345240
申请日：2021-06-11
Applicant: ADOBE INC.
Inventor： Sachin Soni , Siddharth Kumar , Ram Bhushan Agrawal , Ajay Jain
Abstract: Methods and systems are provided for providing directional assistance to guide a user to position a camera for centering a person's face within the camera's field of view. A neural network system is trained to determine the position of the user's face relative to the center of the field of view as captured by an input image. The neural network system is trained using training input images that are generated by cropping different regions of initial training images. Each initial image is used to create a plurality of different training input images, and directional assistance labels used to train the network may be assigned to each training input image based on how the image is cropped. Once trained, the neural network system determines a position of the user's face, and automatically provides a non-visual prompt indicating how to center the face within the field of view.
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