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公开(公告)号：US20180253865A1
公开(公告)日：2018-09-06
申请号：US15448541
申请日：2017-03-02
Applicant: ADOBE SYSTEMS INCORPORATED
Inventor： Brian Lynn Price , Stephen Schiller , Scott Cohen , Ning Xu
CPC classification number: G06T7/194 , G06K9/4604 , G06K9/4652 , G06K2009/366 , G06K2009/4666 , 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：US20150170005A1
公开(公告)日：2015-06-18
申请号：US14107520
申请日：2013-12-16
Applicant: Adobe Systems Incorporated
Inventor： Scott Cohen , Brian Lynn Price , Ejaz Ahmed
CPC classification number: G06F17/30825 , G06F17/30247 , G06F17/30277 , G06F17/3079 , G06K9/00684 , G06K9/6215 , G06K9/6256 , G06K9/6297 , G06T7/11 , G06T7/143 , G06T7/194 , G06T11/60 , G06T2200/24 , G06T2207/20076 , G06T2207/20092
Abstract: Techniques are disclosed herein that enable digital images to be segmented based on a user's semantic input. In other words, given an input image of a person walking a dog adjacent to a tree, a user can simply provide the semantic input “dog” and the system will segment the dog from the other elements in the image. If the user provides other semantic input, such as “person” or “tree”, the system will segment the person or the tree, respectively, from the same image. Using semantic input advantageously eliminates any need for a user to directly interact with the input image through a tedious process of painting brush strokes, tracing boundaries, clicking target points, and/or drawing bounding boxes. Thus semantic input represents an easier and more intuitive way for users to interact with an image segmentation interface, thereby enabling novice users to take advantage of advanced image segmentation techniques.
Abstract translation: 本文公开了使得能够基于用户的语义输入来分割数字图像的技术。 换句话说，给予在与树相邻的人行走的人的输入图像，用户可以简单地提供语义输入“狗”，并且系统将从图像中的其他元素分割狗。 如果用户提供诸如“人”或“树”的其他语义输入，则系统将分别从同一图像中分割人或树。 使用语义输入有利地消除了用户通过绘画画笔笔画，跟踪边界，点击目标点和/或绘制边界框的繁琐过程直接与输入图像交互的任何需要。 因此，语义输入表示用户与图像分割界面交互的更简单和更直观的方式，从而使新手用户能够利用高级图像分割技术。
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Patent Agency Ranking
公开(公告)号：US10255681B2
公开(公告)日：2019-04-09
申请号：US15448541
申请日：2017-03-02
Applicant: ADOBE SYSTEMS INCORPORATED
Inventor： Brian Lynn Price , Stephen Schiller , Scott Cohen , Ning Xu
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：US09129192B2
公开(公告)日：2015-09-08
申请号：US14107601
申请日：2013-12-16
Applicant: Adobe Systems Incorporated
Inventor： Scott Cohen , Brian Lynn Price , Ejaz Ahmed
CPC classification number: G06F17/30277 , G06F17/30247 , G06F17/30825 , G06K9/00684 , G06K9/6215 , G06K9/6256 , G06K9/6297 , G06T7/11 , G06T7/143 , G06T7/194 , G06T11/60 , G06T2200/24 , G06T2207/20076 , G06T2207/20092
Abstract: Techniques are disclosed herein that enable digital images to be segmented based on a user's semantic input. In other words, given an input image of a person walking a dog adjacent to a tree, a user can simply provide the semantic input “dog” and the system will segment the dog from the other elements in the image. If the user provides other semantic input, such as “person” or “tree”, the system will segment the person or the tree, respectively, from the same image. Using semantic input advantageously eliminates any need for a user to directly interact with the input image through a tedious process of painting brush strokes, tracing boundaries, clicking target points, and/or drawing bounding boxes. Thus semantic input represents an easier and more intuitive way for users to interact with an image segmentation interface, thereby enabling novice users to take advantage of advanced image segmentation techniques.
Abstract translation: 本文公开了使得能够基于用户的语义输入来分割数字图像的技术。 换句话说，给予在与树相邻行走的人的输入图像，用户可以简单地提供语义输入“狗”，并且系统将从图像中的其他元素分割狗。 如果用户提供诸如“人”或“树”的其他语义输入，则系统将分别从同一图像中分割人或树。 使用语义输入有利地消除了用户通过绘画画笔笔画，跟踪边界，点击目标点和/或绘制边界框的繁琐过程直接与输入图像交互的任何需要。 因此，语义输入表示用户与图像分割界面交互的更简单和更直观的方式，从而使新手用户能够利用高级图像分割技术。
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公开(公告)号：US20150170006A1
公开(公告)日：2015-06-18
申请号：US14107601
申请日：2013-12-16
Applicant: Adobe Systems Incorporated
Inventor： Scott Cohen , Brian Lynn Price , Ejaz Ahmed
CPC classification number: G06F17/30277 , G06F17/30247 , G06F17/30825 , G06K9/00684 , G06K9/6215 , G06K9/6256 , G06K9/6297 , G06T7/11 , G06T7/143 , G06T7/194 , G06T11/60 , G06T2200/24 , G06T2207/20076 , G06T2207/20092
Abstract: Techniques are disclosed herein that enable digital images to be segmented based on a user's semantic input. In other words, given an input image of a person walking a dog adjacent to a tree, a user can simply provide the semantic input “dog” and the system will segment the dog from the other elements in the image. If the user provides other semantic input, such as “person” or “tree”, the system will segment the person or the tree, respectively, from the same image. Using semantic input advantageously eliminates any need for a user to directly interact with the input image through a tedious process of painting brush strokes, tracing boundaries, clicking target points, and/or drawing bounding boxes. Thus semantic input represents an easier and more intuitive way for users to interact with an image segmentation interface, thereby enabling novice users to take advantage of advanced image segmentation techniques.
Abstract translation: 本文公开了使得能够基于用户的语义输入来分割数字图像的技术。 换句话说，给予在与树相邻行走的人的输入图像，用户可以简单地提供语义输入“狗”，并且系统将从图像中的其他元素分割狗。 如果用户提供诸如“人”或“树”的其他语义输入，则系统将分别从同一图像中分割人或树。 使用语义输入有利地消除了用户通过绘画画笔笔画，跟踪边界，点击目标点和/或绘制边界框的繁琐过程直接与输入图像交互的任何需要。 因此，语义输入表示用户与图像分割界面交互的更简单和更直观的方式，从而使新手用户能够利用高级图像分割技术。
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公开(公告)号：US10223585B2
公开(公告)日：2019-03-05
申请号：US15589484
申请日：2017-05-08
Applicant: Adobe Systems Incorporated
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 comprising drawing commands. The application generates an element proposal for each of many areas on a page of the input document tentatively identified as being page elements. Each of the element proposals may be generated at least in part based on the drawing commands. The page segmentation application classifies each of the element proposals into one of a plurality of defined type of categories of page elements at least in part based on the drawing commands. 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：US09129191B2
公开(公告)日：2015-09-08
申请号：US14107520
申请日：2013-12-16
Applicant: Adobe Systems Incorporated
Inventor： Scott Cohen , Brian Lynn Price , Ejaz Ahmed
CPC classification number: G06F17/30825 , G06F17/30247 , G06F17/30277 , G06F17/3079 , G06K9/00684 , G06K9/6215 , G06K9/6256 , G06K9/6297 , G06T7/11 , G06T7/143 , G06T7/194 , G06T11/60 , G06T2200/24 , G06T2207/20076 , G06T2207/20092
Abstract: Techniques are disclosed herein that enable digital images to be segmented based on a user's semantic input. In other words, given an input image of a person walking a dog adjacent to a tree, a user can simply provide the semantic input “dog” and the system will segment the dog from the other elements in the image. If the user provides other semantic input, such as “person” or “tree”, the system will segment the person or the tree, respectively, from the same image. Using semantic input advantageously eliminates any need for a user to directly interact with the input image through a tedious process of painting brush strokes, tracing boundaries, clicking target points, and/or drawing bounding boxes. Thus semantic input represents an easier and more intuitive way for users to interact with an image segmentation interface, thereby enabling novice users to take advantage of advanced image segmentation techniques.
Abstract translation: 本文公开了使得能够基于用户的语义输入来分割数字图像的技术。 换句话说，给予在与树相邻的人行走的人的输入图像，用户可以简单地提供语义输入“狗”，并且系统将从图像中的其他元素分割狗。 如果用户提供诸如“人”或“树”的其他语义输入，则系统将分别从同一图像中分割人或树。 使用语义输入有利地消除了用户通过绘画画笔笔画，跟踪边界，点击目标点和/或绘制边界框的繁琐过程直接与输入图像交互的任何需要。 因此，语义输入表示用户与图像分割界面交互的更简单和更直观的方式，从而使新手用户能够利用高级图像分割技术。
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