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FRACTAL is a benchmark dataset for 3D point‑cloud semantic segmentation, comprising 100,000 point clouds covering a 250 km² area across five regions in France. Originating from the Lidar HD project, it balances rare classes through an efficient sampling strategy and includes challenging landscapes. Each point cloud spans 50 × 50 m with high point density (average 37 points/m²). The dataset provides seven semantic classes and is colorized using high‑resolution aerial imagery. It is split into training (80,000), validation (10,000), and test (10,000) subsets, with metadata documenting acquisition years and distribution details.
