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公开(公告)号：US10692221B2
公开(公告)日：2020-06-23
申请号：US16035410
申请日：2018-07-13
Applicant: Adobe Inc.
Inventor： I-Ming Pao , Zhe Lin
Abstract: A digital medium environment is described to automatically generate a trimap and segment a digital image, independent of any user intervention. An image processing system receives an image and a low-resolution mask for the image, which provides a probability map indicating a likelihood that a pixel in the image mask corresponds to a foreground object in the image. The image processing system analyzes the image to identify content in the image's foreground and background portions, and adaptively generates a trimap for the image based on differences between the identified foreground and background content. By identifying content of the image prior to generating the trimap, the techniques described herein can be applied to a wide range of images, such as images where foreground content is visually similar to background content, and vice versa. Thus, the image processing system can automatically generate trimaps for images having diverse visual characteristics.
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公开(公告)号：US10592590B2
公开(公告)日：2020-03-17
申请号：US15229108
申请日：2016-08-04
Applicant: ADOBE INC.
Inventor： I-Ming Pao , Alan Lee Erickson , Yuyan Song , Seth Shaw , Hailin Jin , Zhaowen Wang
Abstract: Embodiments of the present invention are directed at providing a font similarity preview for non-resident fonts. In one embodiment, a font is selected on a computing device. In response to the selection of the font, a pre-computed font list is checked to determine what fonts are similar to the selected font. In response to a determination that similar fonts are not local to the computing device, a non-resident font list is sent to a font vendor. The font vendor sends back previews of the non-resident fonts based on entitlement information of a user. Further, a full non-resident font can be synced to the computing device. Other embodiments may be described and/or claimed.
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公开(公告)号：US10515296B2
公开(公告)日：2019-12-24
申请号：US15812548
申请日：2017-11-14
Applicant: Adobe Inc.
Inventor： Yang Liu , Zhaowen Wang , I-Ming Pao , Hailin Jin
Abstract: The present disclosure relates to a font recognition system that employs a multi-task learning framework and training to improve font classification and remove negative side effects caused by intra-class variances of glyph content. For example, in one or more embodiments, the font recognition system trains a hybrid font recognition neural network that includes two or more font recognition neural networks and a weight prediction neural network. The hybrid font recognition neural network determines and generates classification weights based on which font recognition neural network within the hybrid font recognition neural network is best suited to classify the font in an input text image. By employing a hybrid trained font classification neural network, the font recognition system can improve overall font recognition as well as remove the negative side effects from diverse glyph content.
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公开(公告)号：US10430649B2
公开(公告)日：2019-10-01
申请号：US15650669
申请日：2017-07-14
Applicant: Adobe Inc.
Inventor： I-Ming Pao , Jue Wang , Ke Ma , Zhe Lin
Abstract: Text region detection techniques and systems for digital images using image tag filtering are described. These techniques and systems support numerous advantages over conventional techniques through use of image tags to filter text region candidates. A computing device, for instance, may first generate text region candidates through use of a variety of different techniques, such as text line detection. The computing device then assigns image tags to the text region candidates. The assigned image tags are then used by the computing device to filter the text region candidates based on whether image tags assigned to respective candidates are indicative of text.
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公开(公告)号：US20190147304A1
公开(公告)日：2019-05-16
申请号：US15812548
申请日：2017-11-14
Applicant: Adobe Inc.
Inventor： Yang Liu , Zhaowen Wang , I-Ming Pao , Hailin Jin
CPC classification number: G06K9/6828 , G06K9/6227 , G06K9/6257 , G06K9/6262 , G06K9/6277 , G06K9/628 , G06N3/0454 , G06N3/08 , G06N3/084 , G06N5/046
Abstract: The present disclosure relates to a font recognition system that employs a multi-task learning framework and training to improve font classification and remove negative side effects caused by intra-class variances of glyph content. For example, in one or more embodiments, the font recognition system trains a hybrid font recognition neural network that includes two or more font recognition neural networks and a weight prediction neural network. The hybrid font recognition neural network determines and generates classification weights based on which font recognition neural network within the hybrid font recognition neural network is best suited to classify the font in an input text image. By employing a hybrid trained font classification neural network, the font recognition system can improve overall font recognition as well as remove the negative side effects from diverse glyph content.
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Patent Agency Ranking
公开(公告)号：US20230037276A9
公开(公告)日：2023-02-02
申请号：US17233639
申请日：2021-04-19
Applicant: ADOBE INC.
Inventor： Guotong Feng , Alan Erickson , I-Ming Pao , Betty Leong , Hyunghwan Byun
Abstract: Systems and methods for image editing are described. Embodiments of the present disclosure provide an image editing system for performing image object replacement or image region replacement (e.g., an image editing system for replacing an object or region of an image with an object or region from another image). For example, the image editing system may replace a sky portion of an image with a more desirable sky portion from a different replacement image. According to some embodiments described herein, thumbnails, region location information, and image metadata from multiple preset images can be stored together and loaded for presentation and selection of a preset image for replacing a region of an image. Once a preset image (e.g., an image with a replacement sky) is selected, a high-resolution version of the image can be loaded and used to generate a composite image.
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公开(公告)号：US20220335671A1
公开(公告)日：2022-10-20
申请号：US17232890
申请日：2021-04-16
Applicant: ADOBE INC
Inventor： Alan Erickson , Kalyan Sunkavalli , I-Ming Pao , Guotong Feng , Jianming Zhang , Frederick Mandia
Abstract: Systems and methods for image editing are described. Embodiments of the present disclosure provide an image editing system for performing image object replacement or image region replacement (e.g., an image editing system for replacing an object or region of an image with an object or region from another image). For example, the image editing system may replace a sky portion of an image with a more desirable sky portion from a different replacement image. According to some embodiments described herein, real-time color harmonization based on the visible sky region may be used to produce more natural colorization. In some examples, horizon-aware sky alignment and placement with advanced padding may also be used. For example, the horizons of the original image and the replacement image may be automatically detected and aligned, and color harmonization may be performed based on the aligned images.
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公开(公告)号：US10977844B2
公开(公告)日：2021-04-13
申请号：US15826162
申请日：2017-11-29
Applicant: ADOBE INC.
Inventor： Sarah Aye Kong , I-Ming Pao , Hyunghwan Byun
Abstract: Methods and systems are provided for presenting and using multiple masks based on a segmented image in editing the image. In particular, multiple masks can be presented to a user using a graphical user interface for easy selection and utilization in the editing of an image. The graphical user interface can include a display configured to display an image, a mask zone configured to display segmentations of the image using masks, and an edit zone configured to display edits to the image. Upon receiving segmentation for the image, the masks can be displayed in the mask zone where the masks are based on a selected segmentation detail level.
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公开(公告)号：US10783408B2
公开(公告)日：2020-09-22
申请号：US15626749
申请日：2017-06-19
Applicant: Adobe Inc.
Inventor： Zhaowen Wang , Sarah Aye Kong , I-Ming Pao , Hailin Jin , Alan Lee Erickson
IPC: G06K9/68 , G06T7/11 , G06K9/18 , G06K9/66 , G06N3/02 , G06K9/62 , G06N3/08 , G06N3/04 , G06K9/46
Abstract: Systems and techniques for identification of fonts include receiving a selection of an area of an image including text, where the selection is received from within an application. The selected area of the image is input to a font matching module within the application. The font matching module identifies one or more fonts similar to the text in the selected area using a convolutional neural network. The one or more fonts similar to the text are displayed within the application and the selection and use of the one or more fonts is enabled within the application.
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公开(公告)号：US20200020108A1
公开(公告)日：2020-01-16
申请号：US16035410
申请日：2018-07-13
Applicant: Adobe Inc.
Inventor： I-Ming Pao , Zhe Lin
Abstract: A digital medium environment is described to automatically generate a trimap and segment a digital image, independent of any user intervention. An image processing system receives an image and a low-resolution mask for the image, which provides a probability map indicating a likelihood that a pixel in the image mask corresponds to a foreground object in the image. The image processing system analyzes the image to identify content in the image's foreground and background portions, and adaptively generates a trimap for the image based on differences between the identified foreground and background content. By identifying content of the image prior to generating the trimap, the techniques described herein can be applied to a wide range of images, such as images where foreground content is visually similar to background content, and vice versa. Thus, the image processing system can automatically generate trimaps for images having diverse visual characteristics.
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