公开(公告)号：US20250111137A1

公开(公告)日：2025-04-03

申请号：US18477978

申请日：2023-09-29

Applicant: ADOBE INC.

Inventor： Stefan Daniel Dumitrescu ,  Vlad-Constantin Lungu-Stan ,  Ionut Mironica ,  Oliver Brdiczka

IPC: G06F40/186 ,  G06F40/126 ,  G06F40/30 ,  G06F40/40

Abstract: Systems and methods for generating full designs from text include retrieving a plurality of document templates based on a design prompt, and filtering the document templates based on an image prompt. A document template is then selected based on the filtering, and a document is generated based on the document template and the image prompt. Embodiments are further configured to generate content from one or more of the prompts, where the content is included in the final design document.

公开(公告)号：US12267305B2

公开(公告)日：2025-04-01

申请号：US18317338

申请日：2023-05-15

Applicant: Adobe Inc.

Inventor： Nikolaos Barmpalios ,  Ruchi Rajiv Deshpande ,  Randy Lee Swineford ,  Nargol Rezvani ,  Andrew Marc Greene ,  Shawn Alan Gaither ,  Michael Kraley

IPC: H04L9/40 ,  G06N5/04 ,  G06N20/00 ,  G06Q30/0202

Abstract: Systems and techniques for privacy preserving document analysis are described that derive insights pertaining to a digital document without communication of the content of the digital document. To do so, the privacy preserving document analysis techniques described herein capture visual or contextual features of the digital document and creates a stamp representation that represents these features without included the content of the digital document. The stamp representation is projected into a stamp embedding space based on a stamp encoding model generated through machine learning techniques capturing feature patterns and interaction in the stamp representations. The stamp encoding model exploits these feature interactions to define similarity of source documents based on location within the stamp embedding space. Accordingly, the techniques described herein can determine a similarity of documents without having access to the documents themselves.

公开(公告)号：US12265557B2

公开(公告)日：2025-04-01

申请号：US18459081

申请日：2023-08-31

Applicant: Adobe Inc.

Inventor： William Brandon George ,  Wei Zhang ,  Tyler Rasmussen ,  Tung Mai ,  Tong Yu ,  Sungchul Kim ,  Shunan Guo ,  Samuel Nephi Grigg ,  Said Kobeissi ,  Ryan Rossi ,  Ritwik Sinha ,  Eunyee Koh ,  Prithvi Bhutani ,  Jordan Henson Walker ,  Abhisek Trivedi

IPC: G06F40/00 ,  G06F16/242 ,  G06F16/28 ,  G06F40/205 ,  G06F40/40

Abstract: Graphic visualizations, such as charts or graphs conveying data attribute values, can be generated based on natural language queries, i.e., natural language requests. To do so, a natural language request is parsed into n-grams, and from the n-grams, word embeddings are determined using a natural language model. Data attributes for the graphic visualization are discovered in the vector space from the word embeddings. The type of graphic visualization can be determined based on a request intent, which is determined using a trained intent classifier. The graphic visualization is generated to include the data attribute values of the discovered data attributes, and in accordance with the graphic visualization type.

公开(公告)号：US20250104305A1

公开(公告)日：2025-03-27

申请号：US18372625

申请日：2023-09-25

Applicant: Adobe Inc.

Inventor： Sanjeev Tagra ,  Sachin Soni ,  Prasenjit Mondal ,  Ajay Jain

IPC: G06T11/60 ,  G06T7/11 ,  G06T7/73 ,  G06V10/70 ,  G06V40/10

Abstract: Systems and methods are disclosed for reflowing documents to display semantically related content. Embodiments may include receiving a request to view a document that includes body text and one or more images. A trimodal document relationship model identifies relationships between segments of the body text and the one or more images. A linearized view of the document is generated based on the relationships and the linearized view is caused to be displayed on a user device.

公开(公告)号：US20250103822A1

公开(公告)日：2025-03-27

申请号：US18372462

申请日：2023-09-25

Applicant: Adobe Inc.

Inventor： Niranjan Kumbi ,  Sreekanth Reddy ,  Sumit Bhatia ,  Milan Aggarwal ,  Simra Shahid ,  Nikitha Srikanth ,  Camille Girabawe ,  Narayanan Seshadri

IPC: G06F40/35

Abstract: System and methods for generating, validating, and augmenting question-answer pairs using generative AI are provided. An online interaction server accesses a set of digital content available at a set of designated network locations. The online interaction server further trains a pre-trained large language model (LLM) using the set of digital content to obtain a customized LLM. The online interaction server generates a set of question-answer pairs based on the set of digital content using the customized LLM and validates the set of question-answer pairs by determining if an answer in a question-answer pair is derived from the set of digital content. The online interaction server also selects a digital asset to augment an answer in a validated question-answer pair based on a semantic similarity between the validated question-answer pair and the digital asset.

公开(公告)号：US20250103649A1

公开(公告)日：2025-03-27

申请号：US18473045

申请日：2023-09-22

Applicant: Adobe Inc.

Inventor： Ritwik SINHA ,  Viswanathan SWAMINATHAN ,  Simon JENNI ,  Md Mehrab TANJIM ,  John COLLOMOSSE

IPC: G06F16/732 ,  G06F16/738 ,  G06F16/75

Abstract: Embodiments are disclosed for performing content authentication. A method of content authentication may include dividing a query video into a plurality of chunks. A feature vector may be generated, using a fingerprinting model, for each chunk from the plurality of chunks. Similar video chunks are identified from a trusted chunk database based on the feature vectors using a multi-chunk search policy. One or more original videos corresponding to the query video are then returned.

公开(公告)号：US20250095227A1

公开(公告)日：2025-03-20

申请号：US18886452

申请日：2024-09-16

Applicant: ADOBE INC.

Inventor： Adrian-Stefan Ungureanu-Contes ,  Marian Lupascu ,  Vlad-Constantin Lungu-Stan ,  Ionuţ Mironica ,  Vineet Batra

IPC: G06T11/00 ,  G06T3/4053

Abstract: A method, apparatus, non-transitory computer readable medium, and system for training a text-guided vector image synthesis include obtaining training data including a vectorizable image and a caption describing the vectorizable image and generating, using an image generation model, a predicted image with a first level of high frequency detail. Then, the training data and the predicted image are used to tune the image generation model to generate a synthetic vectorizable image based on the caption, where the synthetic vectorizable image has a second level of high frequency detail that is lower than the first level of high frequency detail of the predicted image.

公开(公告)号：US20250086860A1

公开(公告)日：2025-03-13

申请号：US18425335

申请日：2024-01-29

Applicant: Adobe Inc.

Inventor： Varun Manjunatha ,  Vlad Ion Morariu ,  Samyadeep Basu ,  Nanxuan Zhao

IPC: G06T11/60 ,  G06N20/00

Abstract: Knowledge edit techniques for text-to-image models and other generative machine learning models are described. In an example, a location is identified within a text-to-image model by a model edit system. The location is configured to influence generation of a visual attribute by a text-to-image model as part of a digital image. An edited text-to-image model is formed by editing the text-to-image model based on the location. The edit causes a change to the visual attribute in generating a subsequent digital image by the edited text-to-image model. The subsequent digital image is generated as having the change to the visual attribute by the edited text-to-image model.

公开(公告)号：US20250086849A1

公开(公告)日：2025-03-13

申请号：US18463333

申请日：2023-09-08

Applicant: ADOBE INC.

Inventor： Yu Zeng ,  Zhe Lin ,  Jianming Zhang ,  Qing Liu ,  Jason Wen Yong Kuen ,  John Philip Collomosse

IPC: G06T11/00 ,  G06F40/295 ,  G06F40/30 ,  G06V10/774 ,  G06V10/776 ,  G06V20/70

Abstract: Embodiments of the present disclosure include obtaining a text prompt describing an element, layout information indicating a target region for the element, and a precision level corresponding to the element. Some embodiments generate a text feature pyramid based on the text prompt, the layout information, and the precision level, wherein the text feature pyramid comprises a plurality of text feature maps at a plurality of scales, respectively. Then, an image is generated based on the text feature pyramid. In some cases, the image includes an object corresponding to the element of the text prompt at the target region. Additionally, a shape of the object corresponds to a shape of the target region based on the precision level.

公开(公告)号：US20250086373A1

公开(公告)日：2025-03-13

申请号：US18466597

申请日：2023-09-13

Applicant: ADOBE INC.

Inventor： Vivek AGRAWAL ,  Tarun BERI ,  Nitesh DODEJA

IPC: G06F40/103

Abstract: Methods and systems are provided for automated inference and evaluation of design relations for elements of a design. In embodiments described herein, a change, related to a type of design relation, is received to an element of a plurality of elements of a design. A corresponding type of design relation between the element and a different element of the plurality of elements is determined from a knowledge graph based on the type of design relation related to the change. A corresponding change is automatically applied to the different element based on the corresponding type of design relation between the element and the different element.