{"about":{"site":"https://codewithpapers.app","non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page"},"url":"/paper/icdar-2021-competition-on-historical-map","title":"ICDAR 2021 Competition on Historical Map Segmentation","arxiv_id":"2105.13265","date":"2021-05-27","proceeding":null,"authors":["Joseph Chazalon","Edwin Carlinet","Yizi Chen","Julien Perret","Bertrand Duménieu","Clément Mallet","Thierry Géraud","Vincent Nguyen","Nam Nguyen","Josef Baloun","Ladislav Lenc","Pavel Král"],"abstract":"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 \\url{https://icdar21-mapseg.github.io/}.","url_abs":"https://arxiv.org/abs/2105.13265v1","url_pdf":"https://arxiv.org/pdf/2105.13265v1.pdf","source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","row_kind":"abstracts"},"code_links":[{"paper_slug":"icdar-2021-competition-on-historical-map","repo_url":"https://github.com/icdar21-mapseg/icdar21-mapseg-eval","is_official":1,"mentioned_in_paper":0,"mentioned_in_github":0,"framework":"none","reach":null}],"tasks":[{"task_slug":"contour-detection","task_name":"Contour Detection"},{"task_slug":"document-layout-analysis","task_name":"Document Layout Analysis"},{"task_slug":"instance-segmentation","task_name":"Instance Segmentation"},{"task_slug":"line-detection","task_name":"Line Detection"},{"task_slug":"line-segment-detection","task_name":"Line Segment Detection"},{"task_slug":"task-2","task_name":"Task 2"}],"methods":[{"method_slug":"convolution","method_name":"Convolution"},{"method_slug":"fcn","method_name":"FCN"},{"method_slug":"max-pooling","method_name":"Max Pooling"}],"datasets_introduced":[{"slug":"icdar-2021-competition-on-historical-map","name":"ICDAR 2021","full_name":""}],"methods_introduced":[],"results":[],"syntology":{"syntology_url":null,"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}