公开(公告)号：US12056453B2

公开(公告)日：2024-08-06

申请号：US17658855

申请日：2022-04-12

Applicant: ADOBE INC.

Inventor： Ritiz Tambi ,  Rishav Agarwal ,  Rishabh Purwar ,  Ajinkya Gorakhnath Kale ,  Sanyam Jain

IPC: G06F40/20 ,  G06F40/253 ,  G06F40/284 ,  G06F40/35

CPC classification number: G06F40/284 ,  G06F40/253 ,  G06F40/35

Abstract: Systems and methods for natural language processing are described. Embodiments of the present disclosure receive plain text comprising a sequence of text entities; generate a sequence of entity embeddings based on the plain text, wherein each entity embedding in the sequence of entity embeddings is generated based on a text entity in the sequence of text entities; generate style information for the text entity based on the sequence of entity embeddings; and generate a document based on the style information.

公开(公告)号：US20250087006A1

公开(公告)日：2025-03-13

申请号：US18465740

申请日：2023-09-12

Applicant: ADOBE INC.

Inventor： Sanyam JAIN ,  Rishav Agarwal ,  Aditya Garg

IPC: G06V30/194 ,  G06F40/109 ,  G06V30/244 ,  G06V30/412

Abstract: In various embodiments, systems and methods for design-aware replacement font suggestions are provided. In some embodiments, a substitute font-suggestion algorithm holistically considers how the original string of text from the original layout appears when re-rendered in a same-sized text frame using a potential replacement font. In some embodiments, the substitute font-suggestion algorithm generates a first image of a text frame including the text string using the first font and generates a plurality of second images of the text string using candidate replacement fonts. A ranking of the candidate replacement fonts is generated based on computing a score for each of the individual second images that represents similarity between the first image and the individual second images. Based on the assessed similarities, a ranked listing of substitute font suggestions is displayed.

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.

公开(公告)号：US20220156489A1

公开(公告)日：2022-05-19

申请号：US16951983

申请日：2020-11-18

Applicant: Adobe Inc.

Inventor： Rishav Agarwal ,  Rishabh Purwar ,  Abhishek Raj

IPC: G06K9/00 ,  G06N3/04 ,  G06F40/284 ,  G06F40/30 ,  G06F17/18 ,  G06F17/16

Abstract: Methods and systems disclosed herein relate generally to systems and methods for using machine learning techniques to generate section identifiers for one or more sections of the unstructured or unformatted text data. A document-processing application identifies, with a feature-prediction layer of a machine-learning model, a feature representation that represents a semantic structure of a text section within the unformatted and unstructured document. The document-processing application generates, with a sequence-prediction layer of the machine-learning model, a section identifier (e.g., heading, body, list) for a corresponding text section by applying the sequence-prediction layer to the feature representation and using contextual information of neighboring text sections.

公开(公告)号：US12223253B2

公开(公告)日：2025-02-11

申请号：US17984143

申请日：2022-11-09

Applicant: Adobe Inc.

Inventor： Rishav Agarwal ,  Vidisha Rama Hegde ,  Vasu Gupta ,  Sanyam Jain

IPC: G06F17/00 ,  G06F40/103

Abstract: Embodiments are disclosed for real-time copyfitting using a shape of a content area and input text. A content area and an input text for performing copyfitting using a trained classifier is received. A number of remaining characters in the content area is computed in real-time using the input, the computing performed in response to receiving additional input text, wherein computing, in real-time, the number of remaining characters in the content area using the input text includes generating, by the trained classifier, a set of weights including a first set of one or more weights for the input text and a second set of one or more weights for the content area. The first set of one or more weights, the second set of one or more weights, the input text, and the additional input text, and a copyfitting parameter indicating a number of additional characters to be fitted into the content area are determined based on the content area. The copyfitting parameter and the number of remaining characters are presented in real-time.

公开(公告)号：US20230325597A1

公开(公告)日：2023-10-12

申请号：US17658855

申请日：2022-04-12

Applicant: ADOBE INC.

Inventor： Ritiz Tambi ,  Rishav Agarwal ,  Rishabh Purwar ,  Ajinkya Gorakhnath Kale ,  Sanyam Jain

IPC: G06F40/284 ,  G06F40/253 ,  G06F40/35

CPC classification number: G06F40/284 ,  G06F40/253 ,  G06F40/35

Abstract: Systems and methods for natural language processing are described. Embodiments of the present disclosure receive plain text comprising a sequence of text entities; generate a sequence of entity embeddings based on the plain text, wherein each entity embedding in the sequence of entity embeddings is generated based on a text entity in the sequence of text entities; generate style information for the text entity based on the sequence of entity embeddings; and generate a document based on the style information.

公开(公告)号：US11763065B2

公开(公告)日：2023-09-19

申请号：US16662600

申请日：2019-10-24

Applicant: Adobe Inc.

Inventor： Rishav Agarwal ,  Arihant Jain

IPC: G06F40/109 ,  G06F40/106

CPC classification number: G06F40/109 ,  G06F40/106

Abstract: This disclosure involves selecting and applying font features to improve the layout of text. For example, a computing system receives initial text. The computing system calculates an improvement metric representing a layout improvement of a font feature applied to the initial text. The font feature includes replacing a first glyph with a second glyph. The font feature, when applied to the initial text, may result in a layout improvement, which can be quantified using the improvement metric. Based on the calculated improvement metric, the computing system applies the font feature to the initial text to generate updated text. The computing system generates, for display on a display device, the updated text.

公开(公告)号：US20210089614A1

公开(公告)日：2021-03-25

申请号：US16580891

申请日：2019-09-24

Applicant: Adobe Inc.

Inventor： Arihant Jain ,  Rishav Agarwal ,  Gaurav Bhargava

IPC: G06F17/21 ,  G06N20/00 ,  G06K9/62 ,  G06F17/27

Abstract: An automatic content styling system receives digital content, an indication of a style, and an indication of a named entity category. The occurrences of the indicated named entity category in the digital content are identified using a trained machine learning system and the indicated style is automatically applied to the identified occurrences, resulting in styled digital content. User inputs to the styled digital content are also monitored and false positives (occurrences of the indicated named entity category that were not actually the named entity category) and false negatives (occurrences of the indicated named entity category that were not identified) are identified. These false positives and false negatives are used to further train the machine learning system.

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.

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.