Abstract
Animesh Prasad, Hervé Déjean, Jean-Luc Meunier |
International Conference on Document Analysis and Recognition (ICDAR), Sydney, Australia, 20-25 September, 2019 |
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@inproceedings{dejean2019versatile, title={Versatile Layout Understanding via Conjugate Graph}, author={D{\'e}jean, Herv{\'e} and Meunier, Jean-Luc and others}, booktitle={2019 International Conference on Document Analysis and Recognition (ICDAR)}, pages={287--294}, year={2019}, organization={IEEE} }
Abstract
Recent advances in document understanding, especially text recognition, provide new opportunities to address the page segmentation problem. In this paper, we propose a method to groups text lines into semantic objects. We model a page as a graph where nodes represent text lines and the edges their geometric relations. The logical segmentation task then refers to identify all text lines belonging to some logical subdivision of the page. We model this task as categorizing edges as relevant or not to build the targeted sub-division (sub-graph). This edge categorization is performed using structured machine learning algorithms (graph Conditional Random Field and Edge Convolutional Network). We use a connected componentsbased approach following the edge classification for aggregating the nodes. This simple approach shows very robust results for various layout and various page sub-division. We experiment on table segmentation into multiple sub-divisions (rows, columns, and cells) and minutes segmentation into resolutions. Our subdivision and page-layout oblivious approach shows near-par performance as compared to task dedicated approaches and even outperforms them in certain setups.
Details on the gender equality index score 2023 (related to year 2022) for NAVER France of 81/100.
NAVER France targets are as follows:
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Index NAVER France de l’égalité professionnelle entre les femmes et les hommes pour l’année 2023 au titre des données 2022 : 81/100
Détail des indicateurs :
Les objectifs de progression de NAVER France sont :
NAVER LABS Europe 6-8 chemin de Maupertuis 38240 Meylan France Contact
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