icdar-2019 is a state-of-the-art machine learning benchmark indexed on Codesota. This page tracks published model results, top scores per metric, and the SOTA timeline for icdar-2019.
Weighted Average F1 Score is the reported evaluation metric for icdar-2019. Codesota tracks published model scores on this metric so readers can compare state-of-the-art results across sources and model families.
Higher is better
| Rank | Model | Trust | Score | Year | Links | Fix |
|---|---|---|---|---|---|---|
| 01 | DiT-L (Cascade) | verified | 96.55 | 2022 | Paper ↗Code ↗ | Looks wrong? |
| 02 | DiT-B (Cascade) | verified | 96.14 | 2022 | Paper ↗Code ↗ | Looks wrong? |