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retgenai/FOTBCD-Binary

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… See the full description on the dataset page: https://huggingface.co/datasets/retgenai/FOTBCD-Binary.

sourceHugging Facecc-by-nc-sa-4.0updated 7mo agoView on Hugging Face
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Dataset Card

FOTBCD-Binary

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

Dataset Description

PropertyValue
Departments28 (25 train / 3 eval)
Image pairs~28k
Patch size512×512
Resolution0.2m
AnnotationBinary mask

Splits

SplitExamples
train~26k
val~1k
test~1k

Features

FieldTypeDescription
image_idstringUnique identifier
image_beforeImageBefore image (RGB)
image_afterImageAfter image (RGB)
labelImageBinary mask (0=unchanged, 255=changed)
depstringFrench department code
epsgintCoordinate reference system
patch_boundsstringGeographic bounds (JSON)
year_beforeintYear of before image
year_afterintYear of after image

Usage

python
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:

bibtex
@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