Scene Text Recognition on CUTE (test)
93.5AccuracyMATRN
Evaluation Results
| Method | Links | |
|---|---|---|
| MATRN2021.11 | 93.5 | |
| PREN2DYear=20212021.11 | 91.7 | |
| MGP-STR VisionTraining Data=MJ and ST, Lexicon=None2022.09 | 90.63 | |
| RobustScannerYear=20202021.11 | 90.3 | |
| RobustScannerTraining Data=MJ and ST, Lexicon=None2022.09 | 90.3 | |
| MGP-STR FuseTraining Data=MJ and ST, Lexicon=None2022.09 | 90.28 | |
| JVSRYear=20212021.11 | 89.7 | |
| ABINetYear=20212021.11 | 89.2 | |
| ABINetTraining Data=MJ and ST, Lexicon=None2022.09 | 89.2 | |
| ABINet (reproduced)Implementation=reproduced2021.11 | 89 | |
| VisionLANYear=20212021.11 | 88.5 | |
| VisionLANTraining Data=MJ and ST, Lexicon=None2022.09 | 88.5 | |
| Liao et al. (SAM)Backbone=ResNet, Training Data=Synth90K+SynthText, Annotations=word-level, Lexicon=None2020.03 | 87.8 | |
| SRNBackbone=ResNet, Training Data=Synth90K+SynthText, Annotations=word-level, Lexicon=None2020.03 | 87.8 | |
| SATRNYear=20202021.11 | 87.8 | |
| SRNYear=20202021.11 | 87.8 | |
| SATRNTraining Data=MJ and ST, Lexicon=None2022.09 | 87.8 | |
| SRNTraining Data=MJ and ST, Lexicon=None2022.09 | 87.8 | |
| Yang et al. (SCRN)Backbone=ResNet, Training Data=Synth90K+SynthText, Annotations=word and character-level, Lexicon=None2020.03 | 87.5 | |
| GA-SPINYear=20212021.11 | 87.5 | |
| MASTERTraining Data=MJ and ST, Lexicon=None2022.09 | 87.5 | |
| Lyu et al. (Parallel)Backbone=ResNet, Training Data=Synth90K+SynthText, Annotations=word-level, Lexicon=None2020.03 | 86.8 | |
| SAFL2022.01 | 85.4 | |
| Yang et al.Year=20202021.11 | 85.4 | |
| SRN w/o GSRMBackbone=ResNet, Training Data=Synth90K+SynthText, Annotations=word-level, Lexicon=None2020.03 | 84.7 | |
| DANYear=20202021.11 | 84.4 | |
| DANTraining Data=MJ and ST, Lexicon=None2022.09 | 84.4 | |
| STAR-NetTrain Dataset=S90k+ST+TextOCR2021.05 | 83.62 | |
| SE-ASTERYear=20202021.11 | 83.6 | |
| SE-ASTERTraining Data=MJ and ST, Lexicon=None2022.09 | 83.6 | |
| Zhan et al. (ESIR)Backbone=ResNet, Training Data=Synth90K+SynthText, Annotations=word-level, Lexicon=None2020.03 | 83.3 | |
| Li et al. (SAR)Backbone=ResNet, Training Data=Synth90K+SynthText, Annotations=word-level, Lexicon=None2020.03 | 83.3 | |
| SAR2022.01 | 83.3 | |
| ESIR2022.01 | 83.3 | |
| ESIRYear=20192021.11 | 83.3 | |
| ESIRTraining Data=MJ and ST, Lexicon=None2022.09 | 83.3 | |
| TextScannerTraining Data=MJ and ST, Lexicon=None2022.09 | 83.3 | |
| Xie et al. (ACE)Backbone=VGG, Training Data=Synth90K, Annotations=word-level, Lexicon=None2020.03 | 82.6 | |
| ViTSTRTraining Data=MJ and ST, Lexicon=None2022.09 | 81.3 | |
| Liao et al.2022.01 | 79.9 | |
| Shi et al. (ASTER)Backbone=ResNet, Training Data=Synth90K+SynthText, Annotations=word-level, Lexicon=None2020.03 | 79.5 | |
| ASTER2022.01 | 79.5 | |
| TPS-ResNet-BiLSTM-AttnTrain Dataset=S90k+ST+TextOCR2021.05 | 79.44 | |
| RosettaTrain Dataset=S90k+ST+TextOCR2021.05 | 77.35 | |
| Cheng et al. (AON)Backbone=self-designed, Training Data=Synth90K+SynthText, Annotations=word-level, Lexicon=None2020.03 | 76.8 | |
| AON2022.01 | 76.8 | |
| TPS-ResNet-BiLSTM-AttnPW=true, Train Dataset=S90k+ST2021.05 | 74.22 | |
| Baek et al.2022.01 | 74 | |
| TBRATraining Data=MJ and ST, Lexicon=None2022.09 | 74 | |
| CRNNTrain Dataset=S90k+ST+TextOCR2021.05 | 73.87 | |
| STAR-NetPW=true, Train Dataset=S90k+ST2021.05 | 72.47 | |
| CombBestYear=20192021.11 | 71 | |
| TPS-ResNet-BiLSTM-AttnTrain Dataset=TextOCR2021.05 | 70.38 | |
| Yang et al.Backbone=VGG, Training Data=Synth90K+self-made, Annotations=word and character-level, Lexicon=None2020.03 | 69.3 | |
| Yang et al.2022.01 | 69.3 | |
| RosettaPW=true, Train Dataset=S90k+ST2021.05 | 67.6 | |
| CRNNPW=true, Train Dataset=S90k+ST2021.05 | 62.37 | |
| RARE2022.01 | 59.2 | |
| TPS-ResNet-BiLSTM-AttnTrain Dataset=COCOText2021.05 | 50.87 |