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Datasets:
retgenai
/
FOTBCD-Binary

Tasks:
Mask Generation
Image Segmentation
Modalities:
Image
Text
Formats:
parquet
Size:
10K - 100K
ArXiv:
Tags:
Geospatial
Remote Sensing
Building Change Detection
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Datasets
Dask
Polars
License:
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FOTBCD-Binary

A large-scale building change detection benchmark from French orthophotos and topographic data.

Dataset Description

Property Value
Departments 28 (25 train / 3 eval)
Image pairs ~28k
Patch size 512×512
Resolution 0.2m
Annotation Binary mask

Splits

Split Examples
train ~26k
val ~1k
test ~1k

Features

Field Type Description
image_id string Unique identifier
image_before Image Before image (RGB)
image_after Image After image (RGB)
label Image Binary mask (0=unchanged, 255=changed)
dep string French department code
epsg int Coordinate reference system
patch_bounds string Geographic bounds (JSON)
year_before int Year of before image
year_after int Year of after image

Usage 

from datasets import load_dataset

ds = load_dataset("retgenai/FOTBCD-Binary")

example = ds["train"][0]
example["image_before"].show()
example["image_after"].show()
example["label"].show()

License

Citation

If you use FOTBCD in your research, please cite our paper:

@misc{moubane2026fotbcd,
      title={FOTBCD: A Large-Scale Building Change Detection Benchmark from French Orthophotos and Topographic Data},
      author={Abdelrrahman Moubane},
      year={2026},
      eprint={2601.22596},
      archivePrefix={arXiv},
      primaryClass={cs.CV},
      url={https://arxiv.org/abs/2601.22596},
}

Contact

Commercial licensing (FOTBCD-220k): info@retgen.ai
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Size of downloaded dataset files:
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Number of rows:
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Paper for retgenai/FOTBCD-Binary