 HeReceipt-Rotation | 100.00% | 100.00% | 100.00% |
| SCUT-DLVC-Lab-Refinement | 100.00% | 100.00% | 100.00% |
| GREAT-OCR Shanghai University | 100.00% | 100.00% | 100.00% |
| SROIE Fourth Submission | 100.00% | 100.00% | 100.00% |
| Clova OCR | 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% |
| PhucPH | 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% |
| ViTLP | 100.00% | 100.00% | 100.00% |
| Unet and Morphology Prediction | 99.62% | 99.24% | 99.43% |
| EAST modified | 98.11% | 100.00% | 99.05% |
| Pixellink multi-scale Detection | 99.06% | 99.03% | 99.04% |
| Sunshine_OCR | 99.06% | 99.03% | 99.04% |
| Linklogis_BigData | 99.06% | 99.03% | 99.04% |
| Gem AI - OCR Team | 99.06% | 99.03% | 99.04% |
| NetEase OCR | 97.17% | 100.00% | 98.56% |
| 58CV | 100.00% | 97.17% | 98.56% |
| 58 OCR100 | 99.06% | 98.08% | 98.56% |
| MDetector | 99.06% | 98.06% | 98.55% |
| SituTech_OCR | 98.11% | 98.08% | 98.10% |
| A modified CTPN model 2.0 | 98.11% | 98.04% | 98.08% |
| CITlab Argus Textline Detection | 97.92% | 97.69% | 97.81% |
| H&H Lab | 97.17% | 97.12% | 97.14% |
| Ping An Property & Casualty Insurance Company | 97.17% | 97.09% | 97.13% |
| EM_ocr | 97.17% | 97.09% | 97.13% |
| A Single-Shot Model for Robust Text Localization | 94.34% | 100.00% | 97.09% |
| EAST_clip_enhance_896_giou | 93.40% | 98.97% | 96.10% |
| IFLYTEK-textDet_v3 | 95.28% | 96.67% | 95.97% |
| Vsdnu | 93.40% | 97.96% | 95.62% |
| BiLSTM Based on CTPN | 95.28% | 95.35% | 95.32% |
| BOE_IOT_AIBD | 95.28% | 94.95% | 95.12% |
| test_1.7 | 95.28% | 94.34% | 94.81% |
| ICA-IVA | 95.28% | 94.29% | 94.78% |
| Granville ocr | 94.34% | 94.17% | 94.26% |
| EfficientDet and EAST | 92.45% | 95.96% | 94.17% |
| DR Team | 93.21% | 92.88% | 93.05% |
| test_1.6 | 93.40% | 92.45% | 92.92% |
| Unet Segmentation and Watershed | 92.45% | 93.14% | 92.79% |
| base1 | 92.45% | 92.38% | 92.42% |
| base2 | 92.45% | 92.38% | 92.42% |
| base3 | 92.45% | 92.38% | 92.42% |
| A Text Localization Method Based on CTPN | 88.68% | 95.89% | 92.14% |
| Textline detection | 85.85% | 92.86% | 89.22% |
| Improved yolov3 model | 83.96% | 90.63% | 87.17% |
| Yolov3_Autohome | 83.96% | 86.14% | 85.04% |
| base4 | 84.91% | 83.96% | 84.43% |
| test | 84.91% | 83.96% | 84.43% |
| CTPN-SROIE | 76.42% | 89.83% | 82.58% |
| Task 1 - Scanned Receipt Text Localisation (Submitted by Intuit Inc.) | 81.51% | 82.08% | 81.80% |
| YOLO Text Detector | 75.85% | 79.70% | 77.73% |
| Original CRAFT for SROIE | 73.77% | 80.30% | 76.90% |
| MCTPN2 | 70.57% | 77.71% | 73.97% |
| Receipt Info Extracting Task1 zone-dividing | 66.04% | 78.57% | 71.76% |
| Practicing project for Scientific Research Subject (HCMUS master program) | 50.94% | 52.92% | 51.91% |
| scene text detection weapon | 34.53% | 49.58% | 40.71% |