| Unet and Morphology Prediction | 100.00% | 100.00% | 100.00% |
 Ping An Property & Casualty Insurance Company | 100.00% | 100.00% | 100.00% |
| H&H Lab | 100.00% | 100.00% | 100.00% |
| HeReceipt-Rotation | 100.00% | 100.00% | 100.00% |
| SCUT-DLVC-Lab-Refinement | 100.00% | 100.00% | 100.00% |
| A Single-Shot Model for Robust Text Localization | 100.00% | 100.00% | 100.00% |
| Samsung Life Insurance | 100.00% | 100.00% | 100.00% |
| NetEase OCR | 100.00% | 100.00% | 100.00% |
| DR Team | 100.00% | 100.00% | 100.00% |
| Sunshine_OCR | 100.00% | 100.00% | 100.00% |
| Granville ocr | 100.00% | 100.00% | 100.00% |
| A modified CTPN model 1.0 | 100.00% | 100.00% | 100.00% |
| BreSee OCR | 99.59% | 99.20% | 99.40% |
| BOE_AIoT_CTO | 99.59% | 99.17% | 99.38% |
| Gem AI - OCR Team | 99.59% | 99.17% | 99.38% |
| A modified CTPN model 2.0 | 99.59% | 99.17% | 99.38% |
| 58 OCR100 | 97.96% | 100.00% | 98.97% |
| 58CV | 100.00% | 97.92% | 98.95% |
| Linklogis_BigData | 100.00% | 97.92% | 98.95% |
| Linklogis_BeeAI | 100.00% | 97.92% | 98.95% |
| BiLSTM Based on CTPN | 100.00% | 97.87% | 98.92% |
| MDetector | 100.00% | 95.92% | 97.92% |
| only PAN | 97.96% | 95.83% | 96.88% |
| GREAT-OCR Shanghai University | 97.55% | 95.10% | 96.31% |
| EM_ocr | 95.92% | 95.74% | 95.83% |
| Clova OCR | 95.92% | 95.74% | 95.83% |
| MCTPN2 | 95.92% | 93.75% | 94.82% |
| Pixellink multi-scale Detection | 93.88% | 93.62% | 93.75% |
| Yolov3_Autohome | 93.88% | 93.62% | 93.75% |
| BOE_IOT_AIBD | 93.88% | 93.62% | 93.75% |
| EfficientDet and EAST | 93.88% | 93.62% | 93.75% |
| EAST_clip_enhance_896_giou | 91.84% | 95.56% | 93.66% |
| CITlab Argus Textline Detection | 93.47% | 92.92% | 93.19% |
| Textline detection | 93.88% | 91.89% | 92.87% |
| SituTech_OCR | 91.84% | 93.62% | 92.72% |
| IFLYTEK-textDet_v3 | 91.84% | 93.33% | 92.58% |
| A Text Localization Method Based on CTPN | 89.39% | 91.05% | 90.21% |
| EAST modified | 89.80% | 89.58% | 89.69% |
| SROIE Fourth Submission | 89.80% | 89.36% | 89.58% |
| test_1.7 | 89.39% | 86.94% | 88.15% |
| Improved yolov3 model | 87.76% | 87.50% | 87.63% |
| PhucPH | 87.35% | 86.67% | 87.01% |
| ICA-IVA | 87.35% | 83.20% | 85.22% |
| ViTLP | 83.67% | 83.67% | 83.67% |
| test_1.6 | 83.27% | 80.82% | 82.02% |
| YOLO Text Detector | 81.22% | 79.36% | 80.28% |
| base4 | 81.22% | 78.78% | 79.98% |
| test | 81.22% | 78.78% | 79.98% |
| base1 | 79.59% | 75.51% | 77.50% |
| base2 | 79.59% | 75.51% | 77.50% |
| base3 | 79.59% | 75.51% | 77.50% |
| Vsdnu | 75.51% | 77.08% | 76.29% |
| CTPN-SROIE | 73.06% | 77.89% | 75.40% |
| Original CRAFT for SROIE | 71.02% | 71.39% | 71.21% |
| scene text detection weapon | 55.51% | 84.00% | 66.85% |
| Unet Segmentation and Watershed | 57.14% | 52.27% | 54.60% |
| Practicing project for Scientific Research Subject (HCMUS master program) | 53.06% | 52.11% | 52.58% |
| Task 1 - Scanned Receipt Text Localisation (Submitted by Intuit Inc.) | 47.35% | 52.45% | 49.77% |
| Receipt Info Extracting Task1 zone-dividing | 0.00% | 0.00% | 0.00% |