Datasets › SUM

SUM

Introduced by Weixiao Gao et al. in SUM: A Benchmark Dataset of Semantic Urban Meshes27 Feb 2021 archive 2025-07-28

SUM is a new benchmark dataset of semantic urban meshes which covers about 4 km2 in Helsinki (Finland), with six classes: Ground, Vegetation, Building, Water, Vehicle, and Boat.

The authors used Helsinki 3D textured meshes as input and annotated them as a benchmark dataset of semantic urban meshes. The Helsinki's raw dataset covers about 12 km2 and was generated in 2017 from oblique aerial images that have about a 7.5 cm ground sampling distance (GSD) using an off-the-shelf commercial software namely ContextCapture.

The entire region of Helsinki is split into tiles, and each of them covers about 250 m2.

Image source: Gao et al.

Benchmarks archive 2025-07-28

No leaderboard in the archive resolves to this dataset.

Papers archive 2025-07-28

No paper in the archive has a leaderboard row on this dataset; the archive counts 9 papers for it but never published that list.

Dataset loaders archive 2025-07-28

No loader listed in the archive.

Tasks archive 2025-07-28

No task tagged in the archive.

License archive 2025-07-28

No licence recorded in the archive. Absence here is not a statement about the dataset's terms.

Modalities archive 2025-07-28

Languages archive 2025-07-28

No language tagged.

Variants archive 2025-07-28

  • SUM

1 variant name, as the archive lists them.

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