mlsanityData to 14 Oct 2026

ICDAR 2021 Competition on Historical Map Segmentation

arXiv 2105.13265 ↗First posted 27 May 2021cs.CVcited by 5

Not on the map. Why?

Abstract (arXiv)

This paper presents the final results of the ICDAR 2021 Competition on Historical Map Segmentation (MapSeg), encouraging research on a series of historical atlases of Paris, France, drawn at 1/5000 scale between 1894 and 1937. The competition featured three tasks, awarded separately. Task~1 consists in detecting building blocks and was won by the L3IRIS team using a DenseNet-121 network trained in a weakly supervised fashion. This task is evaluated on 3 large images containing hundreds of shapes to detect. Task~2 consists in segmenting map content from the larger map sheet, and was won by the UWB team using a U-Net-like FCN combined with a binarization method to increase detection edge accuracy. Task~3 consists in locating intersection points of geo-referencing lines, and was also won by the UWB team who used a dedicated pipeline combining binarization, line detection with Hough transform, candidate filtering, and template matching for intersection refinement. Tasks~2 and~3 are evaluated on 95 map sheets with complex content. Dataset, evaluation tools and results are available under permissive licensing at urlhttps://icdar21-mapseg.github.io/.

Key facts. Cited by 5 papers in the map (data through 14 Oct 2026). Builds on 4 of its 15 references that are in the map. First posted on arXiv 27 May 2021.

Builds on

4 of 15 references.

References · 4

  1. 2015U-Net: Convolutional Networks for Biomedical Image Segmentationcited by 19,713
  2. 2016Densely Connected Convolutional Networkscited by 6,720
  3. 2018Panoptic Segmentationcited by 802
  4. 2021Hypercorrelation Squeeze for Few-Shot Segmentationcited by 193

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Cited by year

Citing papers per year: 2022: 1; 2023: 1; 2024: 1; 2025: 2.

5 papers.