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Found 4 papers, 2 papers with code
Manifold Mixup improves text recognition with CTC loss
Modern handwritten text recognition techniques employ deep recurrent neural networks.
Adversarial Generation of Handwritten Text Images Conditioned on Sequences
State-of-the-art offline handwriting text recognition systems tend to use neural networks and therefore require a large amount of annotated data to be trained.
Are 2D-LSTM really dead for offline text recognition?
In this work, we aim at a fair comparison between 2D and competing models and also extensively evaluate them on more complex datasets that are more representative of challenging "real-world" data, compared to "academic" datasets that are more restricted in their complexity.
Scan, Attend and Read: End-to-End Handwritten Paragraph Recognition with MDLSTM Attention
We present an attention-based model for end-to-end handwriting recognition.
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