 Ping An Property & Casualty Insurance Company | 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% |
| EM_ocr | 100.00% | 100.00% | 100.00% |
| BOE_AIoT_CTO | 100.00% | 100.00% | 100.00% |
| 58 OCR100 | 100.00% | 100.00% | 100.00% |
| MDetector | 100.00% | 100.00% | 100.00% |
| Sunshine_OCR | 100.00% | 100.00% | 100.00% |
| Linklogis_BigData | 100.00% | 100.00% | 100.00% |
| Granville ocr | 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% |
| NetEase OCR | 99.62% | 99.26% | 99.44% |
| only PAN | 99.62% | 98.91% | 99.26% |
| MCTPN2 | 100.00% | 98.15% | 99.07% |
| Samsung Life Insurance | 98.11% | 100.00% | 99.05% |
| H&H Lab | 99.25% | 98.21% | 98.73% |
| HeReceipt-Rotation | 98.11% | 98.11% | 98.11% |
| BOE_IOT_AIBD | 98.11% | 98.11% | 98.11% |
| Clova OCR | 98.11% | 98.11% | 98.11% |
| A modified CTPN model 2.0 | 98.11% | 98.11% | 98.11% |
| GREAT-OCR Shanghai University | 97.74% | 97.41% | 97.57% |
| CITlab Argus Textline Detection | 97.74% | 97.41% | 97.57% |
| Gem AI - OCR Team | 97.74% | 97.41% | 97.57% |
| EAST_clip_enhance_896_giou | 94.34% | 100.00% | 97.09% |
| BiLSTM Based on CTPN | 94.34% | 100.00% | 97.09% |
| SituTech_OCR | 96.23% | 96.23% | 96.23% |
| EAST modified | 96.23% | 96.23% | 96.23% |
| DR Team | 96.23% | 96.23% | 96.23% |
| PhucPH | 96.23% | 96.23% | 96.23% |
| 58CV | 98.11% | 92.12% | 95.02% |
| ViTLP | 94.34% | 94.34% | 94.34% |
| Vsdnu | 92.45% | 96.08% | 94.23% |
| Textline detection | 92.45% | 95.45% | 93.93% |
| Yolov3_Autohome | 92.45% | 92.45% | 92.45% |
| SROIE Fourth Submission | 92.45% | 92.45% | 92.45% |
| base1 | 92.45% | 92.45% | 92.45% |
| base2 | 92.45% | 92.45% | 92.45% |
| base3 | 92.45% | 92.45% | 92.45% |
| EfficientDet and EAST | 90.57% | 92.31% | 91.43% |
| Pixellink multi-scale Detection | 90.57% | 90.57% | 90.57% |
| Improved yolov3 model | 88.68% | 92.16% | 90.38% |
| test_1.7 | 90.19% | 89.64% | 89.91% |
| test_1.6 | 88.30% | 87.86% | 88.08% |
| IFLYTEK-textDet_v3 | 79.25% | 93.33% | 85.71% |
| base4 | 80.75% | 80.71% | 80.73% |
| test | 80.75% | 80.71% | 80.73% |
| YOLO Text Detector | 80.00% | 80.00% | 80.00% |
| Original CRAFT for SROIE | 76.98% | 75.00% | 75.98% |
| A Text Localization Method Based on CTPN | 69.81% | 76.92% | 73.19% |
| ICA-IVA | 82.64% | 63.71% | 71.95% |
| Unet and Morphology Prediction | 73.58% | 50.00% | 59.54% |
| CTPN-SROIE | 56.60% | 60.53% | 58.50% |
| Unet Segmentation and Watershed | 63.77% | 31.70% | 42.35% |
| Task 1 - Scanned Receipt Text Localisation (Submitted by Intuit Inc.) | 35.47% | 45.58% | 39.90% |
| scene text detection weapon | 31.70% | 38.67% | 34.84% |
| Practicing project for Scientific Research Subject (HCMUS master program) | 29.81% | 31.69% | 30.72% |
| Receipt Info Extracting Task1 zone-dividing | 0.00% | 0.00% | 0.00% |