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Recently, significant progress has been made applying machine learning to the problem of table structure inference and extraction from unstructured documents.
A general method applicable to the search for similarities in the amino acid sequence of two proteins
Saul B Needleman and Christian D Wunsch · 1970
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Tabular abstraction, editing, and formatting, 1996
Xinxin Wang · 1996
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Table structure recognition and its evaluation
Jianying Hu, Ramanujan S Kashi, Daniel P Lopresti, and Gordon Wilfong · 2000
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Why table ground-truthing is hard
Jianying Hu, Ramanujan Kashi, Daniel Lopresti, George Nagy, and Gordon Wilfong · 2001
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Table extraction using conditional random fields
David Pinto, Andrew McCallum, Xing Wei, and W Bruce Croft · 2003
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Learning table extraction from examples
Ashwin Tengli, Yiming Yang, and Nian Li Ma · 2004
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Towards domain-independent information extraction from web tables
Wolfgang Gatterbauer, Paul Bohunsky, Marcus Herzog, Bernhard Krüpl, and Bernhard Pollak · 2007
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Generalized LCS
Amihood Amir, Tzvika Hartman, Oren Kapah, B Riva Shalom, and Dekel Tsur · 2008
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TREX: An approach for recognizing and extracting tables from PDF documents
Ermelinda Oro and Massimo Ruffolo · 2009
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A methodology for evaluating algorithms for table understanding in PDF documents
Max Göbel, Tamir Hassan, Ermelinda Oro, and Giorgio Orsi · 2012
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ICDAR 2013 table competition
Max Göbel, Tamir Hassan, Ermelinda Oro, and Giorgio Orsi · 2013
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Faster R-CNN: Towards real-time object detection with region proposal networks
Shaoqing Ren, Kaiming He, Ross Girshick, and Jian Sun · 2015
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Table understanding using a rule engine
Alexey O Shigarov · 2015
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DeepDeSRT: Deep learning for detection and structure recognition of tables in document images
Rethinking table recognition using graph neural networks
Shah Rukh Qasim, Hassan Mahmood, and Faisal Shafait · 2019
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Image-based table recognition: data, model, and evaluation
Xu Zhong, Elaheh ShafieiBavani, and Antonio Jimeno Yepes · 2019
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End-to-end object detection with transformers
Nicolas Carion, Francisco Massa, Gabriel Synnaeve, Nicolas Usunier, Alexander Kirillov, and Sergey Zagoruyko · 2020
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Tablebank: Table benchmark for image-based table detection and recognition
Minghao Li, Lei Cui, Shaohan Huang, Furu Wei, Ming Zhou, and Zhoujun Li · 2020
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CascadeTabNet: An approach for end to end table detection and structure recognition from image-based documents
Devashish Prasad, Ayan Gadpal, Kshitij Kapadni, Manish Visave, and Kavita Sultanpure · 2020
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Sebastian Schreiber, Stefan Agne, Ivo Wolf, Andreas Dengel, and Sheraz Ahmed · 2017
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Complicated table structure recognition
Zewen Chi, Heyan Huang, Heng-Da Xu, Houjin Yu, Wanxuan Yin, and Xian-Ling Mao · 2019
Cited alongside, same era.
Tablenet: Deep learning model for end-to-end table detection and tabular data extraction from scanned document images
Shubham Singh Paliwal, D Vishwanath, Rohit Rahul, Monika Sharma, and Lovekesh Vig · 2019
Cited alongside, same era.
GriTS: Grid table similarity metric for table structure recognition
Brandon Smock, Rohith Pesala, and Robin Abraham · 2021
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Global table extractor (GTE): A framework for joint table identification and cell structure recognition using visual context
Xinyi Zheng, Douglas Burdick, Lucian Popa, Xu Zhong, and Nancy Xin Ru Wang · 2021
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