Table Detection on ICDAR cTDaR TrackA 2019 (test)
98.4Precision (IoU@0.6)RobusTabNet
Evaluation Results
| Method | Links | |||||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| RobusTabNetProposal=CornerNet, Detector=Faster R-CNN2022.03 | 98.4 | 94 | 96.1 | 98.2 | 93.9 | 96 | 97.7 | 93.3 | 95.4 | 95 | 90.8 | 92.9 | 94.9 | |
| CDeC-Net2022.03 | 98 | 93.9 | 95.9 | 97.7 | 93.6 | 95.6 | 97.1 | 93 | 95 | 93.4 | 89.5 | 91.5 | 94.3 | |
| RPN+FRCNProposal=RPN, Detector=Faster R-CNN2022.03 | 97.8 | 94.8 | 96.3 | 97.3 | 94.3 | 95.7 | 96.3 | 93.3 | 94.7 | 92.4 | 89.5 | 90.9 | 94.1 | |
| TableRadar2022.03 | 97.6 | 96.4 | 97 | 96.6 | 95.4 | 96 | 95.8 | 93.2 | 95.1 | 90.8 | 89.7 | 90.2 | 94.2 | |
| NLPR-PAL2022.03 | 97.1 | 97.5 | 97.3 | 96 | 96.4 | 96.2 | 93.6 | 94 | 93.8 | 86.5 | 86.9 | 86.7 | 92.9 | |
| Lenovo Ocean2022.03 | 91.8 | 90.2 | 90.1 | 90.8 | 89.2 | 90 | 88.5 | 87 | 87.7 | 82.9 | 81.5 | 82.2 | 87.7 | |
| Applica-robots2022.03 | 90.3 | 90.1 | 90.2 | 88.4 | 88.1 | 88.2 | 82.6 | 82.4 | 82.5 | 54.6 | 54.4 | 54.5 | 77 | |
| ABC Fintech2022.03 | 87.4 | 78.5 | 82.7 | 86.3 | 77.5 | 81.7 | 84.1 | 75.5 | 79.6 | 76.8 | 69 | 72.7 | 78.6 |