Crosslingual Handwritten Text Generation Using GANs

Author:

Chang Chun Chieh,Perera Leibny Paola Garcia,Khudanpur Sanjeev

Publisher

Springer Nature Switzerland

Reference34 articles.

1. Alonso, E., Moysset, B., Messina, R.: Adversarial generation of handwritten text images conditioned on sequences. In: 2019 International Conference on Document Analysis and Recognition (ICDAR), pp. 481–486. IEEE Computer Society, Los Alamitos (2019). https://doi.org/10.1109/ICDAR.2019.00083, https://doi.ieeecomputersociety.org/10.1109/ICDAR.2019.00083

2. Bahdanau, D., Cho, K., Bengio, Y.: Neural machine translation by jointly learning to align and translate. CoRR abs/1409.0473 (2014)

3. Brock, A., Donahue, J., Simonyan, K.: Large scale GAN training for high fidelity natural image synthesis. In: International Conference on Learning Representations (2019). https://openreview.net/forum?id=B1xsqj09Fm

4. Carbune, V., et al.: Fast multi-language LSTM-based online handwriting recognition. Int. J. Doc. Anal. Recogn. (IJDAR) 23(2), 89–102 (2020). https://doi.org/10.1007/s10032-020-00350-4

5. CFT SL: Cyrillic handwriting dataset (2022). https://www.kaggle.com/datasets/constantinwerner/cyrillic-handwriting-dataset

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