Links to related benchmarks
Here you can find a list of publicly available benchmarks involving machine learning and computer vision tasks on a moderate to large-scale geospatial datasets:
- ISPRS Benchmarks: semantic labeling. Aerial multi-spectral image data and elevation information.
- IEEE 2015 Data Fusion contest (complete): semantic labeling. Aerial multi-spectral image data, color and 3D point cloud.
- IEEE 2017 Data Fusion contest (complete): local climate-zone prediction. Satellite multi-spectral and multi-temporal image data and vector layers.
- Toronto City Dataset (coming soon): semantic labeling, 3D building reconstruction, road centerline extraction, and others. Aerial image data, ground level imagery, panoramas, and other multi-source information.
- DigitalGlobe SpaceNet, round 2 (live now). Large-scale building footprint extraction. Satellite multi-spectral image data.
- DSTL object detection challenge (kaggle, complete). Satellite multi-spectral image data.
- INRIA aerial image labeling dataset: building segmentation. Aerial image data.
- Semantic3D: Large-scale semantic labeling of 3D point clouds. Ground-level lidar.
- UC Merced dataset: tile-based land-use classification. Satellite image data.
- Zurich Summer Dataset: Semantic segmentation with scarce labels. Satellite acquisitions pansharpened QuickBird.
- Brasilian Coffee plantation dataset: coffee crop classification. Satellite image data.
If you think your dataset belongs to this list, please contact us!