Handwritten Document Recognition
3 papers with code • 0 benchmarks • 0 datasets
Benchmarks
These leaderboards are used to track progress in Handwritten Document Recognition
Most implemented papers
DAN: a Segmentation-free Document Attention Network for Handwritten Document Recognition
For the first time, we propose an end-to-end segmentation-free architecture for the task of handwritten document recognition: the Document Attention Network.
Towards End-to-end Handwritten Document Recognition
We proposed an approach at the line level, based on a fully convolutional network, in order to design a first generic feature extraction step for the handwriting recognition task.
Faster DAN: Multi-target Queries with Document Positional Encoding for End-to-end Handwritten Document Recognition
factodeeplearning/fasterdan
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Recent advances in handwritten text recognition enabled to recognize whole documents in an end-to-end way: the Document Attention Network (DAN) recognizes the characters one after the other through an attention-based prediction process until reaching the end of the document.
