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公开(公告)号：US20210397986A1
公开(公告)日：2021-12-23
申请号：US16904263
申请日：2020-06-17
Applicant: Adobe Inc.
Inventor： Milan Aggarwal , Mausoom Sarkar , Balaji Krishnamurthy
Abstract: Techniques described herein extract form structures from a static form to facilitate making that static form reflowable. A method described herein includes accessing low-level form elements extracted from a static form. The method includes determining, using a first set of prediction models, second-level form elements based on the low-level form elements. Each second-level form element includes a respective one or more low-level form elements. The method further includes determining, using a second set of prediction models, high-level form elements based on the second-level form elements and the low-level form elements. Each high-level form element includes a respective one or more second-level form elements or low-level form elements. The method further includes generating a reflowable form based on the static form by, for each high-level form element, linking together the respective one or more second-level form elements or low-level form elements.
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公开(公告)号：US10268883B2
公开(公告)日：2019-04-23
申请号：US15674100
申请日：2017-08-10
Applicant: Adobe Inc.
Inventor： Mausoom Sarkar , Balaji Krishnamurthy
Abstract: A method and system for detecting and extracting accurate and precise structure in documents. A high-resolution image of documents is segmented into a set of tiles. Each tile is processed by a convolutional network and subsequently by a set of recurrent networks for each row and column. A global-lookup process is disclosed that allows “future” information required for accurate assessment by the recurrent neural networks to be considered. Utilization of high-resolution image allows for precise and accurate feature extraction while segmentation into tiles facilitates the tractable processing of the high-resolution image within reasonable computational resource bounds.
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