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Springer Nature Switzerland
Reference35 articles.
1. Appalaraju, S., Jasani, B., Kota, B.U., Xie, Y., Manmatha, R.: DocFormer: end-to-end transformer for document understanding. In: Proceedings of the IEEE/CVF International Conference on Computer Vision, pp. 993–1003 (2021)
2. Bahdanau, D., Cho, K., Bengio, Y.: Neural machine translation by jointly learning to align and translate (2014). arXiv preprint arXiv:1409.0473
3. Banerjee, A., Biswas, S., Lladós, J., Pal, U.: SwinDocSegmenter: an end-to-end unified domain adaptive transformer for document instance segmentation. In: Fink, G.A., Jain, R., Kise, K., Zanibbi, R. (eds.) Document Analysis and Recognition - ICDAR 2023. ICDAR 2023. LNCS, vol. 14187. Springer, Cham (2023). https://doi.org/10.1007/978-3-031-41676-7_18
4. Biswas, S., Banerjee, A., Lladós, J., Pal, U.: DocSegTr: An instance-level end-to-end document image segmentation transformer (2022). arXiv preprint arXiv:2201.11438
5. Biswas, S., Riba, P., Lladós, J., Pal, U.: Beyond document object detection: instance-level segmentation of complex layouts. Int. J. Doc. Anal. Recogn. (IJDAR) 24(3), 269–281 (2021)