EPFL-ENAC/TOPO-DataGen
[CVPR'22] TOPO-DataGen: an open and scalable aerial synthetic data generation workflow
This workflow helps urban planners, environmental scientists, or drone operators create diverse synthetic visual data from existing geospatial information. You input common geo-data like orthophotos, digital terrain models, or classified point clouds, and it generates synthetic RGB images, 3D scene coordinates, and semantic labels. This is ideal for anyone needing realistic aerial imagery and associated ground truth for tasks like training AI models.
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Use this if you need to generate large, diverse datasets of synthetic aerial imagery with precise 3D geometry, semantic labels, and camera poses for a specific geographic area.
Not ideal if you don't have existing geo-data (like orthophotos or DTMs) for your target area, or if you only need real-world images without synthetic augmentation.
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Dec 02, 2022
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