CMT-Co: Contrastive Learning with Character Movement Task for Handwritten Text Recognition

Author:

Zhang XiaoyiORCID,Wang JiapengORCID,Jin LianwenORCID,Ren YujinORCID,Xue YangORCID

Publisher

Springer Nature Switzerland

Reference46 articles.

1. Aberdam, A., et al.: Sequence-to-sequence contrastive learning for text recognition. In: CVPR, pp. 15302–15312 (2021)

2. Bhunia, A.K., Ghose, S., Kumar, A., Chowdhury, P.N., Sain, A., Song, Y.Z.: MetaHTR: towards writer-adaptive handwritten text recognition. In: CVPR, pp. 15830–15839 (2021)

3. Chen, T., Kornblith, S., Norouzi, M., Hinton, G.: A simple framework for contrastive learning of visual representations. In: ICML, pp. 1597–1607 (2020)

4. Chen, T., Kornblith, S., Swersky, K., Norouzi, M., Hinton, G.E.: Big self-supervised models are strong semi-supervised learners. In: NeurIPS, pp. 22243–22255 (2020)

5. Chen, X., Jin, L., Zhu, Y., Luo, C., Wang, T.: Text recognition in the wild: a survey. ACM Comput. Surv. 54(2), 1–35 (2021)

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