 Textline detection | 100.00% | 100.00% | 100.00% |
| Unet and Morphology Prediction | 100.00% | 100.00% | 100.00% |
| IFLYTEK-textDet_v3 | 100.00% | 100.00% | 100.00% |
| Pixellink multi-scale Detection | 100.00% | 100.00% | 100.00% |
| SituTech_OCR | 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% |
| MCTPN2 | 100.00% | 100.00% | 100.00% |
| GREAT-OCR Shanghai University | 100.00% | 100.00% | 100.00% |
| A Single-Shot Model for Robust Text Localization | 100.00% | 100.00% | 100.00% |
| CITlab Argus Textline Detection | 100.00% | 100.00% | 100.00% |
| SROIE Fourth Submission | 100.00% | 100.00% | 100.00% |
| EM_ocr | 100.00% | 100.00% | 100.00% |
| BOE_IOT_AIBD | 100.00% | 100.00% | 100.00% |
| BOE_AIoT_CTO | 100.00% | 100.00% | 100.00% |
| only PAN | 100.00% | 100.00% | 100.00% |
| Samsung Life Insurance | 100.00% | 100.00% | 100.00% |
| 58 OCR100 | 100.00% | 100.00% | 100.00% |
| DR Team | 100.00% | 100.00% | 100.00% |
| Sunshine_OCR | 100.00% | 100.00% | 100.00% |
| Linklogis_BigData | 100.00% | 100.00% | 100.00% |
| PhucPH | 100.00% | 100.00% | 100.00% |
| Gem AI - OCR Team | 100.00% | 100.00% | 100.00% |
| BreSee OCR | 100.00% | 100.00% | 100.00% |
| Linklogis_BeeAI | 100.00% | 100.00% | 100.00% |
| A modified CTPN model 1.0 | 100.00% | 100.00% | 100.00% |
| A modified CTPN model 2.0 | 100.00% | 100.00% | 100.00% |
| ViTLP | 100.00% | 100.00% | 100.00% |
| NetEase OCR | 98.00% | 100.00% | 98.99% |
| BiLSTM Based on CTPN | 100.00% | 97.73% | 98.85% |
| MDetector | 99.60% | 97.14% | 98.36% |
| Clova OCR | 98.00% | 98.00% | 98.00% |
| Granville ocr | 98.00% | 98.00% | 98.00% |
| 58CV | 98.00% | 97.92% | 97.96% |
| EfficientDet and EAST | 97.20% | 98.40% | 97.80% |
| A Text Localization Method Based on CTPN | 98.00% | 97.50% | 97.75% |
| EAST modified | 96.00% | 95.92% | 95.96% |
| EAST_clip_enhance_896_giou | 92.00% | 97.87% | 94.85% |
| CTPN-SROIE | 94.00% | 94.59% | 94.30% |
| Yolov3_Autohome | 94.00% | 93.88% | 93.94% |
| ICA-IVA | 94.00% | 93.75% | 93.87% |
| test_1.7 | 92.00% | 88.24% | 90.08% |
| test_1.6 | 90.00% | 86.27% | 88.10% |
| scene text detection weapon | 89.20% | 86.57% | 87.86% |
| base1 | 88.00% | 87.50% | 87.75% |
| base2 | 88.00% | 87.50% | 87.75% |
| base3 | 88.00% | 87.50% | 87.75% |
| Vsdnu | 86.00% | 85.42% | 85.71% |
| Improved yolov3 model | 82.00% | 87.23% | 84.54% |
| base4 | 86.00% | 82.35% | 84.14% |
| test | 86.00% | 82.35% | 84.14% |
| Task 1 - Scanned Receipt Text Localisation (Submitted by Intuit Inc.) | 80.80% | 83.53% | 82.14% |
| YOLO Text Detector | 80.00% | 80.00% | 80.00% |
| Original CRAFT for SROIE | 78.40% | 73.57% | 75.91% |
| Practicing project for Scientific Research Subject (HCMUS master program) | 64.00% | 43.20% | 51.58% |
| Unet Segmentation and Watershed | 46.00% | 45.83% | 45.92% |
| Receipt Info Extracting Task1 zone-dividing | 41.20% | 28.68% | 33.82% |