The RDCL2019 test set from the ICDAR 2019 Competition on Recognition of Documents with Complex Layouts. Comprises 85 scanned page images from contemporary magazines and technical/scientific publications (PRImA Layout Analysis Dataset). Evaluation measures region segmentation and classification using Weighted F1-score across layout classes. A continuous competition allowing post-2019 submissions via the Aletheia evaluation tool.
Figure is the reported evaluation metric for document-layout-recognition-challenge-test. 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 | fglihai | verified | 0.97 | 2019 | Source ↗ | Looks wrong? |
| 02 | USYD NLP_CS29-2 | verified | 0.96 | 2019 | Source ↗ | Looks wrong? |
| 03 | Faster R-CNN | verified | 0.95 | 2019 | Source ↗ | Looks wrong? |
Table is the reported evaluation metric for document-layout-recognition-challenge-test. 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 | USYD NLP_CS29-2 | verified | 0.96 | 2019 | Source ↗ | Looks wrong? |
| 02 | fglihai | verified | 0.96 | 2019 | Source ↗ | Looks wrong? |
| 03 | Faster R-CNN | verified | 0.95 | 2019 | Source ↗ | Looks wrong? |
Text is the reported evaluation metric for document-layout-recognition-challenge-test. 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 | USYD NLP_CS29-2 | verified | 0.93 | 2019 | Source ↗ | Looks wrong? |
| 02 | fglihai | verified | 0.93 | 2019 | Source ↗ | Looks wrong? |
| 03 | Faster R-CNN | verified | 0.92 | 2019 | Source ↗ | Looks wrong? |
Overall is the reported evaluation metric for document-layout-recognition-challenge-test. 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 | fglihai | verified | 0.92 | 2019 | Source ↗ | Looks wrong? |
| 02 | USYD NLP_CS29-2 | verified | 0.92 | 2019 | Source ↗ | Looks wrong? |
| 03 | Faster R-CNN | verified | 0.91 | 2019 | Source ↗ | Looks wrong? |
List is the reported evaluation metric for document-layout-recognition-challenge-test. 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 | USYD NLP_CS29-2 | verified | 0.90 | 2019 | Source ↗ | Looks wrong? |
| 02 | fglihai | verified | 0.90 | 2019 | Source ↗ | Looks wrong? |
| 03 | Faster R-CNN | verified | 0.89 | 2019 | Source ↗ | Looks wrong? |
Title is the reported evaluation metric for document-layout-recognition-challenge-test. 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 | fglihai | verified | 0.84 | 2019 | Source ↗ | Looks wrong? |
| 02 | USYD NLP_CS29-2 | verified | 0.84 | 2019 | Source ↗ | Looks wrong? |
| 03 | Faster R-CNN | verified | 0.82 | 2019 | Source ↗ | Looks wrong? |