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公开(公告)号：US20240169145A1
公开(公告)日：2024-05-23
申请号：US18057834
申请日：2022-11-22
Applicant: Adobe Inc.
Inventor： Sanyam Jain , Rishav Agarwal , Rishabh Purwar , Prateek Gaurav , Palak Agrawal , Nikhil Kedia , Ankit Kumar
IPC: G06F40/186 , G06F40/109 , G06T11/60 , G06V30/19 , G06V30/413
CPC classification number: G06F40/186 , G06F40/109 , G06T11/60 , G06V30/19173 , G06V30/413
Abstract: In implementations of systems for stylizing digital content, a computing device implements a style system to receive input data describing digital content to be stylized based on visual styles of example content included in a digital template. The style system generates embeddings for content entities included in the digital content using a machine learning model. Classified content entities are determined based on the embeddings using the machine learning model. The style system generates an output digital template that includes portions of the digital content having the visual styles of example content included in the digital template based on the classified content entities.
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公开(公告)号：US20200151442A1
公开(公告)日：2020-05-14
申请号：US16190466
申请日：2018-11-14
Applicant: Adobe Inc.
Inventor： Monica Singh , Prateek Gaurav , Amish Kumar Bedi
Abstract: The present disclosure relates to systems, methods, and non-transitory computer readable media for generating and providing matching fonts by utilizing a glyph-based machine learning model. For example, the disclosed systems can generate a glyph image by arranging glyphs from a digital document according to an ordering rule. The disclosed systems can further identify target fonts as fonts that include the glyphs within the glyph image. The disclosed systems can further generate target glyph images by arranging glyphs of the target fonts according to the ordering rule. Based on the glyph image and the target glyph images, the disclosed systems can utilize a glyph-based machine learning model to generate and compare glyph image feature vectors. By comparing a glyph image feature vector with a target glyph image feature vector, the font matching system can identify one or more matching glyphs.
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Patent Agency Ranking
公开(公告)号：US20250005275A1
公开(公告)日：2025-01-02
申请号：US18885681
申请日：2024-09-15
Applicant: Adobe Inc.
Inventor： Sanyam Jain , Rishav Agarwal , Rishabh Purwar , Prateek Gaurav , Palak Agrawal , Nikhil Kedia , Ankit Kumar
IPC: G06F40/186 , G06F40/109 , G06T11/60 , G06V30/19 , G06V30/413
Abstract: In implementations of systems for stylizing digital content, a computing device receives digital content having a plurality of content entities. Classified content entities are generated by classifying the plurality of content entities using one or more machine-learning models. A determination is then made regarding correspondence of the classified content entities with visual styles of a digital template. Based on the determined correspondence, the plurality of content entities of the digital content are displayed as having the visual styles, respectively, of the digital template.
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公开(公告)号：US12124794B2
公开(公告)日：2024-10-22
申请号：US18057834
申请日：2022-11-22
Applicant: Adobe Inc.
Inventor： Sanyam Jain , Rishav Agarwal , Rishabh Purwar , Prateek Gaurav , Palak Agrawal , Nikhil Kedia , Ankit Kumar
IPC: G06F40/186 , G06F40/109 , G06T11/60 , G06V30/19 , G06V30/413
CPC classification number: G06F40/186 , G06F40/109 , G06T11/60 , G06V30/19173 , G06V30/413
Abstract: In implementations of systems for stylizing digital content, a computing device implements a style system to receive input data describing digital content to be stylized based on visual styles of example content included in a digital template. The style system generates embeddings for content entities included in the digital content using a machine learning model. Classified content entities are determined based on the embeddings using the machine learning model. The style system generates an output digital template that includes portions of the digital content having the visual styles of example content included in the digital template based on the classified content entities.
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公开(公告)号：US11763583B2
公开(公告)日：2023-09-19
申请号：US17537045
申请日：2021-11-29
Applicant: Adobe Inc.
Inventor： Monica Singh , Prateek Gaurav , Amish Kumar Bedi
IPC: G06V30/244 , G06F16/51 , G06F18/22 , G06F18/214 , G06V10/74 , G06V10/82 , G06V30/28
CPC classification number: G06V30/245 , G06F16/51 , G06F18/2148 , G06F18/22 , G06V10/761 , G06V10/82 , G06V30/293
Abstract: The present disclosure relates to systems, methods, and non-transitory computer readable media for generating and providing matching fonts by utilizing a glyph-based machine learning model. For example, the disclosed systems can generate a glyph image by arranging glyphs from a digital document according to an ordering rule. The disclosed systems can further identify target fonts as fonts that include the glyphs within the glyph image. The disclosed systems can further generate target glyph images by arranging glyphs of the target fonts according to the ordering rule. Based on the glyph image and the target glyph images, the disclosed systems can utilize a glyph-based machine learning model to generate and compare glyph image feature vectors. By comparing a glyph image feature vector with a target glyph image feature vector, the font matching system can identify one or more matching glyphs.
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公开(公告)号：US20220083772A1
公开(公告)日：2022-03-17
申请号：US17537045
申请日：2021-11-29
Applicant: Adobe Inc.
Inventor： Monica Singh , Prateek Gaurav , Amish Kumar Bedi
Abstract: The present disclosure relates to systems, methods, and non-transitory computer readable media for generating and providing matching fonts by utilizing a glyph-based machine learning model. For example, the disclosed systems can generate a glyph image by arranging glyphs from a digital document according to an ordering rule. The disclosed systems can further identify target fonts as fonts that include the glyphs within the glyph image. The disclosed systems can further generate target glyph images by arranging glyphs of the target fonts according to the ordering rule. Based on the glyph image and the target glyph images, the disclosed systems can utilize a glyph-based machine learning model to generate and compare glyph image feature vectors. By comparing a glyph image feature vector with a target glyph image feature vector, the font matching system can identify one or more matching glyphs.
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公开(公告)号：US11216658B2
公开(公告)日：2022-01-04
申请号：US16190466
申请日：2018-11-14
Applicant: Adobe Inc.
Inventor： Monica Singh , Prateek Gaurav , Amish Kumar Bedi
Abstract: The present disclosure relates to systems, methods, and non-transitory computer readable media for generating and providing matching fonts by utilizing a glyph-based machine learning model. For example, the disclosed systems can generate a glyph image by arranging glyphs from a digital document according to an ordering rule. The disclosed systems can further identify target fonts as fonts that include the glyphs within the glyph image. The disclosed systems can further generate target glyph images by arranging glyphs of the target fonts according to the ordering rule. Based on the glyph image and the target glyph images, the disclosed systems can utilize a glyph-based machine learning model to generate and compare glyph image feature vectors. By comparing a glyph image feature vector with a target glyph image feature vector, the font matching system can identify one or more matching glyphs.
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