ICDAR 2024 Competition on Handwriting Recognition of Historical Ciphers
Author:
Publisher
Springer Nature Switzerland
Link
https://link.springer.com/content/pdf/10.1007/978-3-031-70552-6_20
Reference17 articles.
1. Ao, X., Zhang, X.Y., Liu, C.L.: Cross-modal prototype learning for zero-shot handwritten character recognition. Pattern Recogn. 131, 108859 (2022)
2. Lecture Notes in Computer Science;A Baró,2018
3. Bhunia, A.K., Chowdhury, P.N., Yang, Y., Hospedales, T.M., Xiang, T., Song, Y.Z.: Vectorization and rasterization: Self-supervised learning for sketch and handwriting. In: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, pp. 5672–5681 (2021)
4. Gan, J., Wang, W., Leng, J., Gao, X.: Higan+: handwriting imitation GAN with disentangled representations. ACM Trans. Graphics (TOG) 42(1), 1–17 (2022)
5. Hu, W., Zhan, H., Liu, C., Yin, B., Lu, Y.: OTS: a one-shot learning approach for text spotting in historical manuscripts. arXiv preprint arXiv:2304.00746 (2023)
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