 Enetity detection | 100.00% | 100.00% | 100.00% |
| BERT with Multi-task Confidence Prediction | 100.00% | 100.00% | 100.00% |
| H&H Lab | 100.00% | 100.00% | 100.00% |
| HeReceipt-withoutRM | 100.00% | 100.00% | 100.00% |
| PATech_AICenter | 100.00% | 100.00% | 100.00% |
| PICK-PAPCIC & XZMU | 100.00% | 100.00% | 100.00% |
| LayoutLM | 100.00% | 100.00% | 100.00% |
| LayoutLM + Excluding OCR Mismatch | 100.00% | 100.00% | 100.00% |
| HIK_OCR_Exclude_ocr_mismatch | 100.00% | 100.00% | 100.00% |
| Tencent Youtu | 100.00% | 100.00% | 100.00% |
| LayoutLM 2.0 (single model) | 100.00% | 100.00% | 100.00% |
| IE method | 100.00% | 100.00% | 100.00% |
| Applica.ai TILT + Excluding OCR Errors + Fixing total entity | 100.00% | 100.00% | 100.00% |
| IE | 100.00% | 100.00% | 100.00% |
| Linklogis_BeeAI | 100.00% | 100.00% | 100.00% |
| LAKE | 100.00% | 100.00% | 100.00% |
| Character-Aware CNN + Highway + BiLSTM 2.0 | 100.00% | 100.00% | 100.00% |
| GraphRevisedIE | 100.00% | 100.00% | 100.00% |
| loixc-vqa | 100.00% | 100.00% | 100.00% |
| Applica.ai roberta-base-2D | 75.00% | 100.00% | 85.71% |
| Applica.ai Lambert 2.0 + Excluding OCR Mismatch | 75.00% | 100.00% | 85.71% |
| Applica.ai Lambert 2.0 + Excluding OCR Errors + Fixing total entity | 75.00% | 100.00% | 85.71% |
| layoutlm V2 | 75.00% | 100.00% | 85.71% |
| Character-Aware CNN + Highway + BiLSTM 1.0 | 75.00% | 100.00% | 85.71% |
| 1129-clm | 75.00% | 100.00% | 85.71% |
| 1208-cblm | 75.00% | 100.00% | 85.71% |
| 1208-cblm | 75.00% | 100.00% | 85.71% |
| CHL | 75.00% | 100.00% | 85.71% |
| With receipt framing | 75.00% | 75.00% | 75.00% |
| Ping An Property & Casualty Insurance Company | 75.00% | 75.00% | 75.00% |
| BOE_IOT_AIBD | 75.00% | 75.00% | 75.00% |
| ASTRI-CCT-MSA | 75.00% | 75.00% | 75.00% |
| Character & Word BiLSTM Encoder | 75.00% | 75.00% | 75.00% |
| BERT-MRC | 75.00% | 75.00% | 75.00% |
| great | 75.00% | 75.00% | 75.00% |
| Graph Neural Net with Bert Embeddings | 75.00% | 75.00% | 75.00% |
| Token level multi modal bilstm | 75.00% | 75.00% | 75.00% |
| IE + GCN+ OCR | 75.00% | 75.00% | 75.00% |
| GEM AI -OCR TEAM | 75.00% | 75.00% | 75.00% |
| N | 75.00% | 75.00% | 75.00% |
| StrucTexT | 75.00% | 75.00% | 75.00% |
| tixc-vqa | 75.00% | 75.00% | 75.00% |
| PATECH_CHENGDU_OCR | 50.00% | 66.67% | 57.14% |
| RoBERTa-base | 50.00% | 66.67% | 57.14% |
| Multimodal Transformer for Information Extraction | 50.00% | 66.67% | 57.14% |
| Bi-directional LSTM-CNNs-CRF (version2) | 50.00% | 50.00% | 50.00% |
| NER with spaCy model | 50.00% | 50.00% | 50.00% |
| CLOVA OCR | 50.00% | 50.00% | 50.00% |
| IFLYTEK-textNLP_v2 | 50.00% | 50.00% | 50.00% |
| Location-aware BERT model for Text Information Extraction | 50.00% | 50.00% | 50.00% |
| PATECH_CHENGDU_OCR_V2 | 50.00% | 50.00% | 50.00% |
| End-to-end learning with PGN | 50.00% | 50.00% | 50.00% |
| Taikang Insurance Group Research Institute | 50.00% | 50.00% | 50.00% |
| Qubitrics | 50.00% | 50.00% | 50.00% |
| PIC-proj | 50.00% | 50.00% | 50.00% |
| GraphDoc | 50.00% | 50.00% | 50.00% |
| 0 shots | 50.00% | 50.00% | 50.00% |
| 5shout | 50.00% | 50.00% | 50.00% |
| GIE | 25.00% | 50.00% | 33.33% |
| SituTech_OCR | 25.00% | 33.33% | 28.57% |
| RoBERTa-base finetuned on business documents | 25.00% | 33.33% | 28.57% |
| A Simple Method for Key Information Extraction as Character-wise Classification with LSTM | 25.00% | 25.00% | 25.00% |
| GraphLayout | 25.00% | 25.00% | 25.00% |
| test | 25.00% | 25.00% | 25.00% |
| Cool Method Remix | 25.00% | 25.00% | 25.00% |
| Custom Named Entity Recognition | 25.00% | 25.00% | 25.00% |
| coldog | 25.00% | 25.00% | 25.00% |
| lstm deep | 25.00% | 25.00% | 25.00% |
| layoutLMtest | 25.00% | 25.00% | 25.00% |
| 2shot_tem02 | 25.00% | 25.00% | 25.00% |
| 1shot_position | 25.00% | 25.00% | 25.00% |
| Key Information Extraction from Scanned Receipts | 0.00% | 0.00% | 0.00% |
| CITlab Argus Information Extraction (positional & line features, enhanced gt) | 0.00% | 0.00% | 0.00% |
| SROIE LSTM - Axel Alejandro Ramos García | 0.00% | 0.00% | 0.00% |
| lstm standard method trained 100 epochs constant learning rate | 0.00% | 0.00% | 0.00% |
| Character Level BiLSTM | 0.00% | 0.00% | 0.00% |
| Token level bert embed + bilstm | 0.00% | 0.00% | 0.00% |
| test2 | 0.00% | 0.00% | 0.00% |
| test excluding ocr error | 0.00% | 0.00% | 0.00% |
| LSTM without OCRerror and RM | 0.00% | 0.00% | 0.00% |
| LayoutLMv2 | 0.00% | 0.00% | 0.00% |
| Pytesseract + Character Level LSTM + Regex for Dates | 0.00% | 0.00% | 0.00% |