| BreSee OCR | 98.88% | 98.88% | 98.88% |
| Samsung Life Insurance | 97.30% | 98.95% | 98.12% |
| NetEase OCR | 97.30% | 98.68% | 97.99% |
 Ping An Property & Casualty Insurance Company | 97.30% | 97.93% | 97.62% |
| Sunshine_OCR | 96.85% | 97.47% | 97.16% |
| SCUT-DLVC-Lab-Refinement | 96.85% | 97.29% | 97.07% |
| 58CV | 96.85% | 97.29% | 97.07% |
| Linklogis_BeeAI | 96.85% | 97.29% | 97.07% |
| DR Team | 95.51% | 96.56% | 96.03% |
| SROIE Fourth Submission | 96.18% | 95.65% | 95.92% |
| Gem AI - OCR Team | 97.30% | 94.23% | 95.74% |
| H&H Lab | 94.83% | 96.60% | 95.71% |
| Linklogis_BigData | 94.16% | 96.13% | 95.13% |
| Clova OCR | 94.83% | 95.33% | 95.08% |
| BOE_AIoT_CTO | 93.93% | 95.67% | 94.79% |
| MDetector | 93.48% | 96.00% | 94.72% |
| CITlab Argus Textline Detection | 93.93% | 93.48% | 93.70% |
| Granville ocr | 92.36% | 94.89% | 93.61% |
| Pixellink multi-scale Detection | 93.71% | 93.40% | 93.55% |
| GREAT-OCR Shanghai University | 92.58% | 94.47% | 93.52% |
| 58 OCR100 | 92.36% | 94.26% | 93.30% |
| HeReceipt-Rotation | 95.28% | 89.90% | 92.51% |
| only PAN | 87.87% | 95.96% | 91.73% |
| A modified CTPN model 2.0 | 91.24% | 92.20% | 91.72% |
| BOE_IOT_AIBD | 88.54% | 94.63% | 91.49% |
| SituTech_OCR | 88.54% | 92.41% | 90.44% |
| EM_ocr | 87.87% | 91.83% | 89.80% |
| A Single-Shot Model for Robust Text Localization | 84.04% | 95.70% | 89.49% |
| IFLYTEK-textDet_v3 | 81.57% | 98.90% | 89.41% |
| A modified CTPN model 1.0 | 89.44% | 87.14% | 88.28% |
| ViTLP | 87.42% | 88.31% | 87.86% |
| test_1.7 | 88.31% | 80.20% | 84.06% |
| EAST modified | 79.55% | 87.14% | 83.17% |
| test_1.6 | 84.94% | 77.20% | 80.89% |
| PhucPH | 78.43% | 82.07% | 80.21% |
| EfficientDet and EAST | 72.81% | 87.37% | 79.43% |
| base1 | 78.65% | 79.55% | 79.10% |
| base2 | 78.65% | 79.55% | 79.10% |
| base3 | 78.65% | 79.55% | 79.10% |
| ICA-IVA | 76.63% | 80.24% | 78.39% |
| EAST_clip_enhance_896_giou | 72.81% | 84.05% | 78.03% |
| Unet Segmentation and Watershed | 82.02% | 74.16% | 77.89% |
| YOLO Text Detector | 73.71% | 80.00% | 76.73% |
| base4 | 80.67% | 72.60% | 76.42% |
| test | 80.67% | 72.60% | 76.42% |
| Vsdnu | 69.21% | 80.00% | 74.22% |
| Unet and Morphology Prediction | 75.28% | 70.59% | 72.86% |
| Receipt Info Extracting Task1 zone-dividing | 71.91% | 70.69% | 71.29% |
| Textline detection | 64.49% | 75.56% | 69.59% |
| A Text Localization Method Based on CTPN | 63.37% | 75.94% | 69.09% |
| BiLSTM Based on CTPN | 63.60% | 75.32% | 68.96% |
| Yolov3_Autohome | 62.47% | 63.04% | 62.76% |
| MCTPN2 | 59.10% | 64.52% | 61.69% |
| CTPN-SROIE | 47.87% | 65.82% | 55.42% |
| scene text detection weapon | 52.13% | 58.92% | 55.32% |
| Task 1 - Scanned Receipt Text Localisation (Submitted by Intuit Inc.) | 58.43% | 45.91% | 51.42% |
| Improved yolov3 model | 31.69% | 49.23% | 38.56% |
| Original CRAFT for SROIE | 44.94% | 31.92% | 37.33% |
| Practicing project for Scientific Research Subject (HCMUS master program) | 20.90% | 12.63% | 15.74% |