Deep Learning for Table Detection and Structure Recognition: A Survey
Salaheldin Kasem M. Abdallah A. Berendeyev A. Elkady E. Mahmoud M. Abdalla M. Hamada M. Vascon S. Nurseitov D. Taj-Eddin I.
3 October 2024Association for Computing Machinery
ACM Computing Surveys
2024#56Issue 12
Tables are everywhere, from scientific journals, articles, websites, and newspapers all the way to items we buy at the supermarket. Detecting them is thus of utmost importance to automatically understanding the content of a document. The performance of table detection has substantially increased thanks to the rapid development of deep learning networks. The goals of this survey are to provide a profound comprehension of the major developments in the field of Table Detection, offer insight into the different methodologies, and provide a systematic taxonomy of the different approaches. Furthermore, we provide an analysis of both classic and new applications in the field. Lastly, the datasets and source code of the existing models are organized to provide the reader with a compass on this vast literature. Finally, we go over the architecture of utilizing various object detection and table structure recognition methods to create an effective and efficient system, as well as a set of development trends to keep up with state-of-the-art algorithms and future research. We have also set up a public GitHub repository where we will be updating the most recent publications, open data, and source code. The GitHub repository is available at https://github.com/abdoelsayed2016/table-detection-structure-recognition.
Additional Key Words and PhrasesConvolutional neural networks , deep learning , table detection , table structure recognition
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Faculty of Computers and Information, Assiut University, Assiut, Egypt
Chungbuk National University, Cheongju, South Korea
Ca Foscari University of Venice, Venezia, Veneto, Italy
Satbayev University, Almaty, Kazakhstan
College of Electrical and Computer Engineering, Chungbuk National University, Cheongju, Chungcheongbuk-do, South Korea
Information Technology Institute, Alexandria, Cairo, Egypt
Department of Information System, International IT University, Almaty, Kazakhstan
JSC NC KazMunayGas, Astana, Kazakhstan
Faculty of Computers and Information
Chungbuk National University
Ca Foscari University of Venice
Satbayev University
College of Electrical and Computer Engineering
Information Technology Institute
Department of Information System
JSC NC KazMunayGas
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