Document Information Extraction via Global Tagging

Author:

He ShaojieORCID,Wang TianshuORCID,Lu YaojieORCID,Lin HongyuORCID,Han XianpeiORCID,Sun YingfeiORCID,Sun LeORCID

Publisher

Springer Nature Singapore

Reference26 articles.

1. Appalaraju, S., Jasani, B., Kota, B.U., Xie, Y., Manmatha, R.: DocFormer: end-to-end transformer for document understanding. In: 2021 IEEE/CVF International Conference on Computer Vision, ICCV 2021, Montreal, QC, Canada, 10–17 October 2021, pp. 973–983. IEEE (2021). https://doi.org/10.1109/ICCV48922.2021.00103

2. Cao, H., et al.: GMN: generative multi-modal network for practical document information extraction. In: Carpuat, M., de Marneffe, M., Ruíz, I.V.M. (eds.) Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, NAACL 2022, Seattle, WA, United States, 10–15 July 2022, pp. 3768–3778. Association for Computational Linguistics (2022). https://doi.org/10.18653/v1/2022.naacl-main.276

3. Cheng, Z., et al.: TRIE++: towards end-to-end information extraction from visually rich documents. CoRR (2022). https://doi.org/10.48550/arXiv.2207.06744

4. Davis, B.L., Morse, B.S., Price, B.L., Tensmeyer, C., Wigington, C., Morariu, V.I.: End-to-end document recognition and understanding with Dessurt. In: Karlinsky, L., Michaeli, T., Nishino, K. (eds.) Computer Vision - ECCV 2022 Workshops - Tel Aviv, Israel, 23–27 October 2022, Proceedings, Part IV. LNCS, vol. 13804, pp. 280–296. Springer, Cham (2022). https://doi.org/10.1007/978-3-031-25069-9_19

5. Denk, T.I., Reisswig, C.: BERTgrid: contextualized embedding for 2D document representation and understanding. In: Workshop on Document Intelligence at NeurIPS 2019 (2019). https://openreview.net/forum?id=H1gsGaq9US

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