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In this paper, we propose a new class of metric for table structure recognition (TSR) evaluation, called grid table similarity (GriTS).
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Corrêa, A.S., Zander, P.O.: Unleashing tabular content to open data: A survey on pdf table extraction methods and tools. In: Proceedings of the 18th Annual International Conference on Digital Government Research. pp. 54–63 (2017)
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Gao, L., Huang, Y., Déjean, H., Meunier, J.L., Yan, Q., Fang, Y., Kleber, F., Lang, E.: ICDAR 2019 competition on table detection and recognition (cTDaR). In: 2019 International Conference on Document Analysis and Recognition (ICDAR). pp. 1510–1515. IEEE (2019)
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Göbel, M., Hassan, T., Oro, E., Orsi, G.: A methodology for evaluating algorithms for table understanding in PDF documents. In: Proceedings of the 2012 ACM symposium on Document engineering. pp. 45–48 (2012)
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Harutyunyan, A., Borradaile, G., Chambers, C., Scaffidi, C.: Planted-model evaluation of algorithms for identifying differences between spreadsheets. In: 2012 IEEE Symposium on Visual Languages and Human-Centric Computing (VL/HCC). pp. 7–14. IEEE (2012)
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Li, M., Cui, L., Huang, S., Wei, F., Zhou, M., Li, Z.: Tablebank: Table benchmark for image-based table detection and recognition. In: Proceedings of The 12th Language Resources and Evaluation Conference. pp. 1918–1925 (2020)
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Smock, B., Pesala, R., Abraham, R.: PubTables-1M: Towards comprehensive table extraction from unstructured documents. In: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR). pp. 4634–4642 (June 2022)
2022
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