| 01 | CLIP4STR-L (DataComp-1B) From paper: CLIP4STR: A Simple Baseline for Scene Text Recognition with Pre-trained Vision-Language Model | verified | 99.6 | 2023 | Paper ↗Code ↗ | Looks wrong? |
| 02 | DTrOCR 105M From paper: DTrOCR: Decoder-only Transformer for Optical Character Recognition | verified | 99.6 | 2023 | Paper ↗Code ↗ | Looks wrong? |
| 03 | CLIP4STR-B (DataComp-1B) From paper: CLIP4STR: A Simple Baseline for Scene Text Recognition with Pre-trained Vision-Language Model | verified | 99.5 | 2023 | Paper ↗Code ↗ | Looks wrong? |
| 04 | CLIP4STR-L From paper: CLIP4STR: A Simple Baseline for Scene Text Recognition with Pre-trained Vision-Language Model | verified | 99.5 | 2023 | Paper ↗Code ↗ | Looks wrong? |
| 05 | CPPD From paper: Context Perception Parallel Decoder for Scene Text Recognition | verified | 99.3 | 2023 | Paper ↗Code ↗ | Looks wrong? |
| 06 | CLIP4STR-B From paper: CLIP4STR: A Simple Baseline for Scene Text Recognition with Pre-trained Vision-Language Model | verified | 99.2 | 2023 | Paper ↗Code ↗ | Looks wrong? |
| 07 | PARSeq Lowercase alphanum eval, 3000 test samples. ECCV 2022. | verified | 99 | 2022 | Paper ↗ | Looks wrong? |
| 08 | MGP-STR From paper: Multi-Granularity Prediction for Scene Text Recognition | verified | 98.8 | 2022 | Paper ↗Code ↗ | Looks wrong? |
| 09 | CCD-ViT-Small(ARD_2.8M) From paper: Self-supervised Character-to-Character Distillation for Text Recognition | verified | 98 | 2022 | Paper ↗Code ↗ | Looks wrong? |
| 10 | CCD-ViT-Base(ARD_2.8M) From paper: Self-supervised Character-to-Character Distillation for Text Recognition | verified | 98 | 2022 | Paper ↗Code ↗ | Looks wrong? |
| 11 | S-GTR From paper: Visual Semantics Allow for Textual Reasoning Better in Scene Text Recognition | verified | 97.5 | 2021 | Paper ↗Code ↗ | Looks wrong? |
| 12 | DiffusionSTR From paper: DiffusionSTR: Diffusion Model for Scene Text Recognition | verified | 97.3 | 2023 | Paper ↗ | Looks wrong? |
| 13 | CCD-ViT-Tiny(ARD_2.8M) From paper: Self-supervised Character-to-Character Distillation for Text Recognition | verified | 97.1 | 2022 | Paper ↗Code ↗ | Looks wrong? |
| 14 | SIGA_S From paper: Self-supervised Implicit Glyph Attention for Text Recognition | verified | 96.9 | 2022 | Paper ↗Code ↗ | Looks wrong? |
| 15 | MATRN From paper: Multi-modal Text Recognition Networks: Interactive Enhancements between Visual and Semantic Features | verified | 96.6 | 2021 | Paper ↗Code ↗ | Looks wrong? |
| 16 | CDistNet (Ours) From paper: CDistNet: Perceiving Multi-Domain Character Distance for Robust Text Recognition | verified | 96.57 | 2021 | Paper ↗Code ↗ | Looks wrong? |
| 17 | ABINet-LV ABINet Language-Vision variant. CVPR 2021. | verified | 96.4 | 2021 | Paper ↗ | Looks wrong? |
| 18 | DPAN From paper: Look Back Again: Dual Parallel Attention Network for Accurate and Robust Scene Text Recognition | verified | 96.2 | 2021 | Paper ↗Code ↗ | Looks wrong? |
| 19 | TrOCR-large 558M TrOCR-large, Syn+Benchmark training. Table 6. AAAI 2023. | verified | 94.1 | 2021 | Paper ↗ | Looks wrong? |
| 20 | TrOCR-base 334M TrOCR-base, Syn+Benchmark training. Table 6. AAAI 2023. | verified | 93.4 | 2021 | Paper ↗ | Looks wrong? |
| 21 | CRNN Lexicon-free. Table 2. TPAMI 2017. | verified | 78.2 | 2015 | Paper ↗ | Looks wrong? |