Papers › FLAIR #1: semantic segmentation and domain adaptation dataset

FLAIR #1: semantic segmentation and domain adaptation dataset

23 Nov 2022arXiv:2211.12979archive 2025-07-28

Anatol Garioud, Stéphane Peillet, Eva Bookjans, Sébastien Giordano, Boris Wattrelos

The French National Institute of Geographical and Forest Information (IGN) has the mission to document and measure land-cover on French territory and provides referential geographical datasets, including high-resolution aerial images and topographic maps. The monitoring of land-cover plays a crucial role in land management and planning initiatives, which can have significant socio-economic and environmental impact. Together with remote sensing technologies, artificial intelligence (IA) promises to become a powerful tool in determining land-cover and its evolution. IGN is currently exploring the potential of IA in the production of high-resolution land cover maps. Notably, deep learning methods are employed to obtain a semantic segmentation of aerial images. However, territories as large as France imply heterogeneous contexts: variations in landscapes and image acquisition make it challenging to provide uniform, reliable and accurate results across all of France. The FLAIR-one dataset presented is part of the dataset currently used at IGN to establish the French national reference land cover map "Occupation du sol \`a grande \'echelle" (OCS- GE).

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read_config IGNF/FLAIR-1-AI-Challenge/src/flair/utils.py official repository ran Apache-2.0 (permissive) · f99b92265e606433 · report
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train IGNF/FLAIR-1-AI-Challenge/src/flair/tasks.py official repository unverified Apache-2.0 (permissive) · a583fc74263240ea · report

Tasks

Domain AdaptationManagementSemantic Segmentation

Datasets

Introduced by this paper, per the archive.

FLAIR (French Land cover from Aerospace ImageRy)

Results from the paper archive 2025-07-28

TaskDatasetModelMetricValueRank at snapshotLeaderboardReport
Semantic Segmentation FLAIR (French Land cover from Aerospace ImageRy) U-Net baseline mIoU 0.557 #5 of 5 Archive leaderboard report

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