Model ICDAR 2021 24M
MapSeg21 Baseline U-Net for Historical Map Segmentation
Reported evaluation
| Dataset | Split | Metric | Score |
|---|---|---|---|
| MapSeg21 | test | COCO PQ (building blocks) | 0.62 |
| MapSeg21 | test | mean IoU (map content) | 0.91 |
Downloads
| File | Type | Size | Mirrors |
|---|---|---|---|
|
mapseg-baseline-unet.pt
Pre-trained PyTorch weights (baseline reference)
|
weights | 92 MB | Mirror 1 |
|
README.md
Model card and usage instructions
|
model-card | — | Mirror 1 |
Description
A reference U-Net baseline released alongside the ICDAR 2021 MapSeg competition. The model is trained to perform two of the three competition tasks (building-block detection and map-content segmentation) on 1894-1937 atlas sheets of the City of Paris.
It is published primarily as a sanity-check baseline so that participants in any future re-run of the competition can confirm their data loading and evaluation pipeline against a known reference, not as a state-of-the-art model.
See the companion dataset and the evaluation tools for the full reproducible pipeline.
Note: this entry is illustrative for the catalog prototype; the weights file listed above is a placeholder URL, not a real download.