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original_paper.md 1.08 KiB
Original implementation
The paper is available at https://arxiv.org/abs/2203.12273.
This model focuses on handwritten text and layout recognition through the use of an end-to-end segmentation-free attention-based network. DAN was evaluated on two public datasets: RIMES and READ 2016 at single-page and double-page levels.
The following results were published:
| CER (%) | WER (%) | LOER (%) | mAP_cer (%) | |
|---|---|---|---|---|
| RIMES (single page) | 4.54 | 11.85 | 3.82 | 93.74 |
| READ 2016 (single page) | 3.53 | 13.33 | 5.94 | 92.57 |
| READ 2016 (double page) | 3.69 | 14.20 | 4.60 | 93.92 |
Pretrained model weights are available here.