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公开(公告)号:US11829710B2
公开(公告)日:2023-11-28
申请号:US17583818
申请日:2022-01-25
Applicant: Adobe Inc.
Inventor: Oliver Brdiczka , Sanat Sharma , Jayant Kumar , Alexandru Vasile Costin , Aliakbar Darabi , Kushith Amerasinghe
IPC: G06F40/166 , G06F40/106 , G06F16/58 , G06F40/12 , G06F16/38 , G06V30/413
CPC classification number: G06F40/166 , G06F16/5866 , G06F40/106 , G06F40/12 , G06F16/38 , G06V30/413
Abstract: An illustrator system accesses a multi-element document, the multi-element document including a plurality of elements. The illustrator system determines, for each of the plurality of elements, an element-specific topic distribution comprising a ranked list of topics. The illustrator system creates a first aggregated topic distribution from the determined element-specific topic distributions. The illustrator system determines a global intent for the multi-element document, the global intent including one or more terms from the first aggregated topic distribution. The illustrator system queries a database using the global intent to retrieve a substitute element. The illustrator system generates a replacement multi-element document that includes a substitute element in place of an element in the multi-element document The at least one substitute element is different from the element in the displayed multi-element document.
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公开(公告)号:US20230080407A1
公开(公告)日:2023-03-16
申请号:US17475145
申请日:2021-09-14
Applicant: Adobe Inc.
Inventor: Jayant Kumar , Manasi Deshmukh , Ming Liu , Ashok Gupta , Karthik Suresh , Chirag Arora , Jing Zheng , Ravindra Sadaphule , Vipul Dalal , Andrei Stefan
Abstract: This disclosure describes methods, non-transitory computer readable storage media, and systems that generate a digital knowledge graph based on a plurality of tutorial content items to generate recommendations of digital resource items. Specifically, the disclosed system extracts a plurality of tasks, subject categories related to the tasks, and context signals related to an environment for the tasks from a plurality of tutorial content items for one or more digital content editing applications. The disclosed system generates a digital knowledge graph including nodes corresponding to the tasks and subject categories connected via edges based on relationships extracted from the tutorial content items. In some embodiments, the disclosed system also includes nodes corresponding to digital resource items in the digital knowledge graph or in a subgraph. The disclosed system utilizes the digital knowledge graph with context data to provide a recommendation of digital resource items for display at a client device.
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公开(公告)号:US20220253435A1
公开(公告)日:2022-08-11
申请号:US17172986
申请日:2021-02-10
Applicant: ADOBE INC.
Inventor: Fengbin Chen , Venkat Barakam , Benjamin Leviant , Amine Ben Khalifa , Kerem Turgutlu , Jayant Kumar , Sumeet Zaverilal Gala , Gaurav Kukal , Vipul Dalal
IPC: G06F16/245 , G06N3/04 , G06N3/08
Abstract: Systems and methods for information retrieval are described. Embodiments generate a dense embedding for each of a plurality of media objects to be searched, generate a sparse embedding for each of the media objects using an encoder that takes the dense embedding as an input, wherein the sparse embedding satisfies a sparsity constraint that is applied to at least one layer of the encoder during training, and perform a search on the plurality of media objects based at least in part on the sparse embedding.
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公开(公告)号:US20210272253A1
公开(公告)日:2021-09-02
申请号:US16803332
申请日:2020-02-27
Applicant: Adobe Inc.
Inventor: Zhe Lin , Vipul Dalal , Vera Lychagina , Shabnam Ghadar , Saeid Motiian , Rohith mohan Dodle , Prethebha Chandrasegaran , Mina Doroudi , Midhun Harikumar , Kannan Iyer , Jayant Kumar , Gaurav Kukal , Daniel Miranda , Charles R. McKinney , Archit Kalra
Abstract: The present disclosure relates to an image merging system that automatically and seamlessly detects and merges missing people for a set of digital images into a composite group photo. For instance, the image merging system utilizes a number of models and operations to automatically analyze multiple digital images to identify a missing person from a base image, segment the missing person from the second image, and generate a composite group photo by merging the segmented image of the missing person into the base image. In this manner, the image merging system automatically creates merged group photos that appear natural and realistic.
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公开(公告)号:US20200342255A1
公开(公告)日:2020-10-29
申请号:US16928949
申请日:2020-07-14
Applicant: Adobe Inc.
Inventor: Jayant Kumar , Zhe Lin , Vipulkumar C. Dalal
IPC: G06K9/62
Abstract: There is described a computing device and method in a digital medium environment for custom auto tagging of multiple objects. The computing device includes an object detection network and multiple image classification networks. An image is received at the object detection network and includes multiple visual objects. First feature maps are applied to the image at the object detection network and generate object regions associated with the visual objects. The object regions are assigned to the multiple image classification networks, and each image classification network is assigned to a particular object region. The second feature maps are applied to each object region at each image classification network, and each image classification network outputs one or more classes associated with a visual object corresponding to each object region.
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公开(公告)号:US20200026956A1
公开(公告)日:2020-01-23
申请号:US16039311
申请日:2018-07-18
Applicant: Adobe Inc.
Inventor: Jayant Kumar , Zhe Lin , Vipulkumar C. Dalal
IPC: G06K9/62
Abstract: There is described a computing device and method in a digital medium environment for custom auto tagging of multiple objects. The computing device includes an object detection network and multiple image classification networks. An image is received at the object detection network and includes multiple visual objects. First feature maps are applied to the image at the object detection network and generate object regions associated with the visual objects. The object regions are assigned to the multiple image classification networks, and each image classification network is assigned to a particular object region. The second feature maps are applied to each object region at each image classification network, and each image classification network outputs one or more classes associated with a visual object corresponding to each object region.
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公开(公告)号:US20230274478A1
公开(公告)日:2023-08-31
申请号:US17652512
申请日:2022-02-25
Applicant: ADOBE INC.
Inventor: Kerem Can Turgutlu , Sanat Sharma , Jayant Kumar , Rohith Mohan Dodle , Vipul Dalal
IPC: G06T11/60 , G06V10/764 , G06V20/70 , G06V10/774 , G06V10/82
CPC classification number: G06T11/60 , G06V10/764 , G06V20/70 , G06V10/774 , G06V10/82 , G06T2210/12 , G06T2210/61
Abstract: Systems and methods for image processing are described. Embodiments of the present disclosure receive an image depicting an object; generate a sequence of tokens including a set of tokens corresponding to the object and a set of mask tokens corresponding to an additional object to be inserted into the image; generate a placement token value for the set of mask tokens based on the sequence of tokens using a sequence encoder, wherein the placement token value represents position information of the additional object; and insert the additional object into the image based on the position information to obtain a composite image.
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公开(公告)号:US11574392B2
公开(公告)日:2023-02-07
申请号:US16803332
申请日:2020-02-27
Applicant: Adobe Inc.
Inventor: Zhe Lin , Vipul Dalal , Vera Lychagina , Shabnam Ghadar , Saeid Motiian , Rohith mohan Dodle , Prethebha Chandrasegaran , Mina Doroudi , Midhun Harikumar , Kannan Iyer , Jayant Kumar , Gaurav Kukal , Daniel Miranda , Charles R McKinney , Archit Kalra
Abstract: The present disclosure relates to an image merging system that automatically and seamlessly detects and merges missing people for a set of digital images into a composite group photo. For instance, the image merging system utilizes a number of models and operations to automatically analyze multiple digital images to identify a missing person from a base image, segment the missing person from the second image, and generate a composite group photo by merging the segmented image of the missing person into the base image. In this manner, the image merging system automatically creates merged group photos that appear natural and realistic.
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公开(公告)号:US20220351513A1
公开(公告)日:2022-11-03
申请号:US17865076
申请日:2022-07-14
Applicant: Adobe Inc.
Inventor: Jayant Kumar , Vera Lychagina , Tarun Vashisth , Sudhakar Pandey , Sharad Mangalick , Rohith Mohan Dodle , Peter Baust , Mina Doroudi , Kerem Turgutlu , Kannan Iyer , Gaurav Kukal , Archit Kalra , Amine Ben Khalifa
Abstract: Disclosed are systems and methods for dynamically determining categories for images. A computer-implemented method may include training a neural network to receive an input image and determine one or more image categories associated with the input image; obtaining a set of images associated with a user; determining, using the trained neural network, one or more image categories associated with each image included in the obtained set of images; determining one or more dominant image categories associated with the user based on the determined image categories for the obtained set of images; and determining an image editing user interface for the user based on the determined one or more dominant image categories.
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公开(公告)号:US11971885B2
公开(公告)日:2024-04-30
申请号:US17172986
申请日:2021-02-10
Applicant: ADOBE INC.
Inventor: Fengbin Chen , Venkat Barakam , Benjamin Leviant , Amine Ben Khalifa , Kerem Turgutlu , Jayant Kumar , Sumeet Zaverilal Gala , Gaurav Kukal , Vipul Dalal
IPC: G06F16/00 , G06F16/245 , G06N3/04 , G06N3/08
CPC classification number: G06F16/245 , G06N3/04 , G06N3/08
Abstract: Systems and methods for information retrieval are described. Embodiments generate a dense embedding for each of a plurality of media objects to be searched, generate a sparse embedding for each of the media objects using an encoder that takes the dense embedding as an input, wherein the sparse embedding satisfies a sparsity constraint that is applied to at least one layer of the encoder during training, and perform a search on the plurality of media objects based at least in part on the sparse embedding.
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