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公开(公告)号：US20230196014A1
公开(公告)日：2023-06-22
申请号：US18112136
申请日：2023-02-21
Applicant: Adobe Inc.
IPC: G06F40/253 , G06F40/44 , G06F40/166
CPC classification number: G06F40/253 , G06F40/44 , G06F40/166 , G06N5/022
Abstract: Rewriting text in the writing style of a target author is described. A stylistic rewriting system receives input text and an indication of the target author. The system trains a language model to understand the target author's writing style using a corpus of text associated with the target author. The language model may be transformer-based, and is first trained on a different corpus of text associated with a range of different authors to understand linguistic nuances of a particular language. Copies of the language model are then cascaded into an encoder-decoder framework, which is further trained using a masked language modeling objective and a noisy version of the target author corpus. After training, the encoder-decoder framework of the trained language model automatically rewrites input text in the writing style of the target author and outputs the rewritten text as stylized text.
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公开(公告)号：US11670085B2
公开(公告)日：2023-06-06
申请号：US17090013
申请日：2020-11-05
Applicant: Adobe Inc.
Inventor： Gaurav Verma , Balaji Vasan Srinivasan , Trikay Nalamada , Pranav Goel , Keerti Harpavat , Aman Mishra
IPC: G06V20/40 , G11B27/34 , G11B27/034
CPC classification number: G06V20/47 , G06V20/41 , G06V20/49 , G11B27/034 , G11B27/34
Abstract: A method for personalized playback of a video as performed by a video platform includes parsing a video into segments based on visual and audio content of the video. The platform creates multimodal fragments that represent underlying segments of the video, and then orders the multimodal fragments based on a preference of a target user. The platform thus enables nonlinear playback of the segmented video in accordance with the multimodal fragments.
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公开(公告)号：US11610054B1
公开(公告)日：2023-03-21
申请号：US17450250
申请日：2021-10-07
Applicant: Adobe Inc.
Inventor： Vinay Aggarwal , Vishwa Vinay , Rizurekh Saha , Prabhat Mahapatra , Niyati Himanshu Chhaya , Harshit Agrawal , Chloe McConnell , Bhanu Prakash Reddy Guda , Balaji Vasan Srinivasan
IPC: G06F40/186 , G06F40/109 , G06K9/62 , G06F40/30 , G06N20/00
Abstract: Techniques for template generation from image content includes extracting information associated with an input image. The information comprises: 1) layout information indicating positions of content corresponding to a content type of a plurality of content types within the input image; and 2) text attributes indicating at least a font of text included in the input image. A user-editable template having the characteristics of the input image is generated based on the layout information and the text attributes.
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公开(公告)号：US20220230061A1
公开(公告)日：2022-07-21
申请号：US17153130
申请日：2021-01-20
Applicant: Adobe Inc.
Inventor： Hrituraj Singh , Jatin Lamba , Denil Pareshbhai Mehta , Balaji Vasan Srinivasan , Anshul Nasery , Aishwarya Agarwal
Abstract: In some embodiments, a multimodal computing system receives a query and identifies, from source documents, text passages and images that are relevant to the query. The multimodal computing system accesses a multimodal question-answering model that includes a textual stream of language models and a visual stream of language models. Each of the textual stream and the visual stream contains a set of transformer-based models and each transformer-based model includes a cross-attention layer using data generated by both the textual stream and visual stream of language models as an input. The multimodal computing system identifies text relevant to the query by applying the textual stream to the text passages and computes, using the visual stream, relevance scores of the images to the query, respectively. The multimodal computing system further generates a response to the query by including the text and/or an image according to the relevance scores.
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65.发明申请公开(公告)号：US20220075965A1
公开(公告)日：2022-03-10
申请号：US17529886
申请日：2021-11-18
Applicant: ADOBE INC.
Inventor： Balaji Vasan Srinivasan , Anandhavelu Natarajan , Abhilasha Sancheti
Abstract: Embodiments of the present disclosure are directed to a system, methods, and computer-readable media for facilitating stylistic expression transfers in machine translation of source sequence data. Using integrated loss functions for style transfer along with content preservation and/or cross entropy, source sequence data is processed by an autoencoder trained to reduce loss values across the loss functions at each time step encoded for the source sequence data. The target sequence data generated by the autoencoder therefore exhibits reduced loss values for the integrated loss functions at each time step, thereby improving content preservation and providing for stylistic expression transfer.
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Patent Agency Ranking
公开(公告)号：US11157693B2
公开(公告)日：2021-10-26
申请号：US16800018
申请日：2020-02-25
Applicant: Adobe Inc.
IPC: G06F40/253 , G06F40/44 , G06F40/166 , G06N5/02 , G06F40/169 , G06F40/289 , G06K9/00 , G06F17/00
Abstract: Rewriting text in the writing style of a target author is described. A stylistic rewriting system receives input text and an indication of the target author. The system trains a language model to understand the target author's writing style using a corpus of text associated with the target author. The language model may be transformer-based, and is first trained on a different corpus of text associated with a range of different authors to understand linguistic nuances of a particular language. Copies of the language model are then cascaded into an encoder-decoder framework, which is further trained using a masked language modeling objective and a noisy version of the target author corpus. After training, the encoder-decoder framework of the trained language model automatically rewrites input text in the writing style of the target author and outputs the rewritten text as stylized text.
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公开(公告)号：US20210294978A1
公开(公告)日：2021-09-23
申请号：US16825864
申请日：2020-03-20
Applicant: Adobe Inc.
Inventor： Niyati Himanshu Chhaya , Sopan Khosla , Balaji Vasan Srinivasan
IPC: G06F40/30 , G06N3/04 , G06N3/08 , G06F40/289
Abstract: A digital attribution system is described to generate predictions of word attributions from subject data, e.g., titles, subject lines of emails, and so on. To do so, an attribution score is first generated by the digital attribution system that describe an amount to which respective words in the subject data cause performance of a corresponding outcome. The attribution scores are then used by the digital attribution system to generate representations for display in a user interface for respective words in the subject data and may also be used to generate attribution recommendations of changes to be made to the subject data.
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公开(公告)号：US20210279269A1
公开(公告)日：2021-09-09
申请号：US16809222
申请日：2020-03-04
Applicant: Adobe Inc.
Inventor： Gaurav Verma , Suryateja B V , Samagra Sharma , Balaji Vasan Srinivasan
IPC: G06F16/48 , G06F40/30 , G06F16/435 , G06F16/44 , G06F16/2457
Abstract: Implementations are described for content fragments aligned to content criteria to enable rich sets of multimodal content to be generated based on specified content criteria, such as content needs pertaining to various content delivery platforms and scenarios. For instance, the described techniques take a set of content (e.g., text, images, etc.) along with a specified content criteria (e.g., business/user need) and creates content fragment variants that are tailored to the content criteria with respect to both the information presented as well as the style of the content presented.
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公开(公告)号：US11023577B2
公开(公告)日：2021-06-01
申请号：US15228570
申请日：2016-08-04
Applicant: ADOBE INC.
Inventor： Shiv Kumar Saini , Natwar Modani , Balaji Vasan Srinivasan
Abstract: In various implementations, a method includes receiving a set of time series data that corresponds to a metric. A seasonal pattern is extracted from the set of time series data and the extracted seasonal pattern is filtered from the set of time series data. A predictive model is generated from the filtered set of data. The extracted seasonal pattern is filtered from another set of time series data where the second set of time series data corresponds to the metric. The filtered second set of time series data is compared to the predictive model. An alert is generated to a user for a value within the filtered second set of time series data which falls outside of the predictive model.
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公开(公告)号：US10984172B2
公开(公告)日：2021-04-20
申请号：US17008570
申请日：2020-08-31
Applicant: Adobe Inc.
Inventor： Balaji Vasan Srinivasan , Vishwa Vinay , Niyati Chhaya , Cedric Huesler
IPC: G06F40/106 , G06F40/186 , G06F40/14
Abstract: The present disclosure includes systems, methods, and non-transitory computer readable media that utilize a genetic framework to generate enhanced digital layouts from digital content fragments. In particular, in one or more embodiments, the disclosed systems iteratively generate a layout chromosome of digital content fragments, determine a fitness level of the layout chromosome, and mutate the layout chromosome until converging to an improved fitness level. The disclosed systems can efficiently utilize computing resources to generate a digital layout from a layout chromosome that is optimized to specified platforms, distribution audiences, and target optimization goals.
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