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Scene Text Recognition On Ic19 Art
Metrics
Accuracy (%)
Results
Performance results of various models on this benchmark
| Paper Title | Repository | ||
|---|---|---|---|
| CLIP4STR-L (DataComp-1B) | 86.4 | CLIP4STR: A Simple Baseline for Scene Text Recognition with Pre-trained Vision-Language Model | |
| CLIP4STR-L | 85.9 | CLIP4STR: A Simple Baseline for Scene Text Recognition with Pre-trained Vision-Language Model | |
| CLIP4STR-B | 85.8 | CLIP4STR: A Simple Baseline for Scene Text Recognition with Pre-trained Vision-Language Model | |
| MGP-STR | 85.5 | Multi-Granularity Prediction for Scene Text Recognition | |
| PARSeq | 84.5±0.1 | Scene Text Recognition with Permuted Autoregressive Sequence Models |
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