Handwritten Text Recognition On Lam Line
Metrics
Test CER
Test WER
Results
Performance results of various models on this benchmark
Model Name | Test CER | Test WER | Paper Title | Repository |
---|---|---|---|---|
TrOCR | 3.6 | 11.6 | TrOCR: Transformer-based Optical Character Recognition with Pre-trained Models | |
GFCN | 5.2 | 18.5 | Recurrence-free unconstrained handwritten text recognition using gated fully convolutional network | |
OrigamiNet-18 | 3.1 | 11.1 | OrigamiNet: Weakly-Supervised, Segmentation-Free, One-Step, Full Page Text Recognition by learning to unfold | |
OrigamiNet-24 | 3.0 | 11.0 | OrigamiNet: Weakly-Supervised, Segmentation-Free, One-Step, Full Page Text Recognition by learning to unfold | |
OrigamiNet-12 | 3.1 | 11.2 | OrigamiNet: Weakly-Supervised, Segmentation-Free, One-Step, Full Page Text Recognition by learning to unfold | |
HTR-VT | 2.8 | 7.4 | HTR-VT: Handwritten Text Recognition with Vision Transformer |
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