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公开(公告)号：US11244460B2
公开(公告)日：2022-02-08
申请号：US16822853
申请日：2020-03-18
Applicant: Adobe Inc.
Inventor： Brian Lynn Price , Peng Zhou , Scott David Cohen , Gregg Darryl Wilensky
Abstract: In implementations of object boundary generation, a computing device implements a boundary system to receive a mask defining a contour of an object depicted in a digital image, the mask having a lower resolution than the digital image. The boundary system maps a curve to the contour of the object and extracts strips of pixels from the digital image which are normal to points of the curve. A sample of the digital image is generated using the extracted strips of pixels which is input to a machine learning model. The machine learning model outputs a representation of a boundary of the object by processing the sample of the digital image.
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公开(公告)号：US20210166013A1
公开(公告)日：2021-06-03
申请号：US16701586
申请日：2019-12-03
Applicant: ADOBE INC.
Inventor： Christopher Alan Tensmeyer , Rajiv Jain , Curtis Michael Wigington , Brian Lynn Price , Brian Lafayette Davis
IPC: G06K9/00 , G06F3/0488 , G06N3/04 , G06N3/08 , G06K9/22
Abstract: Techniques are provided for generating a digital image of simulated handwriting using an encoder-decoder neural network trained on images of natural handwriting samples. The simulated handwriting image can be generated based on a style of a handwriting sample and a variable length coded text input. The style represents visually distinctive characteristics of the handwriting sample, such as the shape, size, slope, and spacing of the letters, characters, or other markings in the handwriting sample. The resulting simulated handwriting image can include the text input rendered in the style of the handwriting sample. The distinctive visual appearance of the letters or words in the simulated handwriting image mimics the visual appearance of the letters or words in the handwriting sample image, whether the letters or words in the simulated handwriting image are the same as in the handwriting sample image or different from those in the handwriting sample image.
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公开(公告)号：US11004208B2
公开(公告)日：2021-05-11
申请号：US16365213
申请日：2019-03-26
Applicant: Adobe Inc.
Inventor： Brian Lynn Price , Scott Cohen , Marco Forte , Ning Xu
Abstract: Techniques are disclosed for deep neural network (DNN) based interactive image matting. A methodology implementing the techniques according to an embodiment includes generating, by the DNN, an alpha matte associated with an image, based on user-specified foreground region locations in the image. The method further includes applying a first DNN subnetwork to the image, the first subnetwork trained to generate a binary mask based on the user input, the binary mask designating pixels of the image as background or foreground. The method further includes applying a second DNN subnetwork to the generated binary mask, the second subnetwork trained to generate a trimap based on the user input, the trimap designating pixels of the image as background, foreground, or uncertain status. The method further includes applying a third DNN subnetwork to the generated trimap, the third subnetwork trained to generate the alpha matte based on the user input.
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公开(公告)号：US20200311946A1
公开(公告)日：2020-10-01
申请号：US16365213
申请日：2019-03-26
Applicant: Adobe Inc.
Inventor： Brian Lynn Price , Scott Cohen , Marco Forte , Ning Xu
Abstract: Techniques are disclosed for deep neural network (DNN) based interactive image matting. A methodology implementing the techniques according to an embodiment includes generating, by the DNN, an alpha matte associated with an image, based on user-specified foreground region locations in the image. The method further includes applying a first DNN subnetwork to the image, the first subnetwork trained to generate a binary mask based on the user input, the binary mask designating pixels of the image as background or foreground. The method further includes applying a second DNN subnetwork to the generated binary mask, the second subnetwork trained to generate a trimap based on the user input, the trimap designating pixels of the image as background, foreground, or uncertain status. The method further includes applying a third DNN subnetwork to the generated trimap, the third subnetwork trained to generate the alpha matte based on the user input.
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公开(公告)号：US10699111B2
公开(公告)日：2020-06-30
申请号：US16251568
申请日：2019-01-18
Applicant: Adobe Inc.
Inventor： Scott Cohen , Brian Lynn Price , Dafang He , Michael F. Kraley , Paul Asente
Abstract: Disclosed systems and methods generate page segmented documents from unstructured vector graphics documents. The page segmentation application executing on a computing device receives as input an unstructured vector graphics document. The application generates an element proposal for each of many areas on a page of the input document tentatively identified as being page elements. The page segmentation application classifies each of the element proposals into one of a plurality of defined type of categories of page elements. The page segmentation application may further refine at least one of the element proposals and select a final element proposal for each element within the unstructured vector document. One or more of the page segmentation steps may be performed using a neural network.
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Patent Agency Ranking
公开(公告)号：US20200151444A1
公开(公告)日：2020-05-14
申请号：US16191158
申请日：2018-11-14
Applicant: Adobe Inc.
Inventor： Brian Lynn Price , Vlad Ion Morariu , Scott David Cohen , Christopher Alan Tensmeyer
Abstract: A table layout determination system implemented on a computing device obtains an image of a table having multiple cells. The table layout determination system includes a row prediction machine learning system that generates, for each of multiple rows of pixels in the image of the table, a probability of the row being a row separator, and a column prediction machine learning system generates, for each of multiple columns of pixels in the image of the table, a probability of the column being a column separator. An inference system uses these probabilities of the rows being row separators and the columns being column separators to identify the row separators and column separators for the table. These row separators and column separators are the layout of the table.
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公开(公告)号：US20190220983A1
公开(公告)日：2019-07-18
申请号：US16359880
申请日：2019-03-20
Applicant: ADOBE INC.
Inventor： Brian Lynn Price , Stephen Schiller , Scott Cohen , Ning Xu
CPC classification number: G06T7/194 , G06K9/4604 , G06K9/4652 , G06K2009/366 , G06K2009/4666 , G06N3/0454 , G06N3/084 , G06N3/088 , G06T7/11 , G06T7/90 , G06T2207/10024 , G06T2207/20081 , G06T2207/20084
Abstract: Methods and systems are provided for generating mattes for input images. A neural network system can be trained where the training includes training a first neural network that generates mattes for input images where the input images are synthetic composite images. Such a neural network system can further be trained where the training includes training a second neural network that generates refined mattes from the mattes produced by the first neural network. Such a trained neural network system can be used to input an image and trimap pair for which the trained system will output a matte. Such a matte can be used to extract an object from the input image. Upon extracting the object, a user can manipulate the object, for example, to composite the object onto a new background.
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公开(公告)号：US20190156115A1
公开(公告)日：2019-05-23
申请号：US16251568
申请日：2019-01-18
Applicant: Adobe Inc.
Inventor： Scott Cohen , Brian Lynn Price , Dafang He , Michael F. Kraley , Paul Asente
CPC classification number: G06K9/00456 , G06K9/00463 , G06K9/3233 , G06K9/342 , G06K9/4628 , G06K9/6256 , G06K9/627 , G06N3/0454 , G06N3/08
Abstract: Disclosed systems and methods generate page segmented documents from unstructured vector graphics documents. The page segmentation application executing on a computing device receives as input an unstructured vector graphics document. The application generates an element proposal for each of many areas on a page of the input document tentatively identified as being page elements. The page segmentation application classifies each of the element proposals into one of a plurality of defined type of categories of page elements. The page segmentation application may further refine at least one of the element proposals and select a final element proposal for each element within the unstructured vector document. One or more of the page segmentation steps may be performed using a neural network.
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公开(公告)号：US12229399B2
公开(公告)日：2025-02-18
申请号：US18420444
申请日：2024-01-23
Applicant: Adobe Inc.
Inventor： Christopher Alan Tensmeyer , Rajiv Jain , Curtis Michael Wigington , Brian Lynn Price , Brian Lafayette Davis
IPC: G06F3/048 , G06F3/04883 , G06N3/045 , G06N3/08 , G06V10/44 , G06V10/82 , G06V30/226 , G06V30/228 , G06V30/32
Abstract: Techniques are provided for generating a digital image of simulated handwriting using an encoder-decoder neural network trained on images of natural handwriting samples. The simulated handwriting image can be generated based on a style of a handwriting sample and a variable length coded text input. The style represents visually distinctive characteristics of the handwriting sample, such as the shape, size, slope, and spacing of the letters, characters, or other markings in the handwriting sample. The resulting simulated handwriting image can include the text input rendered in the style of the handwriting sample. The distinctive visual appearance of the letters or words in the simulated handwriting image mimics the visual appearance of the letters or words in the handwriting sample image, whether the letters or words in the simulated handwriting image are the same as in the handwriting sample image or different from those in the handwriting sample image.
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公开(公告)号：US20240168625A1
公开(公告)日：2024-05-23
申请号：US18420444
申请日：2024-01-23
Applicant: Adobe Inc.
Inventor： Christopher Alan Tensmeyer , Rajiv Jain , Curtis Michael Wigington , Brian Lynn Price , Brian Lafayette Davis
IPC: G06F3/04883 , G06N3/045 , G06N3/08 , G06V10/44 , G06V10/82 , G06V30/226 , G06V30/228 , G06V30/32
CPC classification number: G06F3/04883 , G06N3/045 , G06N3/08 , G06V10/454 , G06V10/82 , G06V30/2264 , G06V30/2276 , G06V30/228 , G06V30/347
Abstract: Techniques are provided for generating a digital image of simulated handwriting using an encoder-decoder neural network trained on images of natural handwriting samples. The simulated handwriting image can be generated based on a style of a handwriting sample and a variable length coded text input. The style represents visually distinctive characteristics of the handwriting sample, such as the shape, size, slope, and spacing of the letters, characters, or other markings in the handwriting sample. The resulting simulated handwriting image can include the text input rendered in the style of the handwriting sample. The distinctive visual appearance of the letters or words in the simulated handwriting image mimics the visual appearance of the letters or words in the handwriting sample image, whether the letters or words in the simulated handwriting image are the same as in the handwriting sample image or different from those in the handwriting sample image.
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