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SotA/Methodology/Optical Character Recognition (OCR)/Benchmarking Chinese Text Recognition: Datasets, Baselines, and an Empirical Study

Optical Character Recognition (OCR) on Benchmarking Chinese Text Recognition: Datasets, Baselines, and an Empirical Study

Metric: Accuracy (%) (higher is better)

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#Model↕Accuracy (%)▼AugmentationsPaperDate↕Code
1DTrOCR89.6NoDTrOCR: Decoder-only Transformer for Optical Cha...2023-08-30Code
2DTrOCR 105M89.6NoDTrOCR: Decoder-only Transformer for Optical Cha...2023-08-30Code
3MaskOCR-L82.6NoMaskOCR: Text Recognition with Masked Encoder-De...2022-06-01-
4TransOCR72.8No--Code
5SRN65NoTowards Accurate Scene Text Recognition with Sem...2020-03-27Code
6MORAN64.3NoA Multi-Object Rectified Attention Network for S...2019-01-10Code
7SEED61.2NoSEED: Semantics Enhanced Encoder-Decoder Framewo...2020-05-22Code