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.