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A novel retrieval framework boosts aerial-ground LiDAR place recognition accuracy by nearly 10%, tackling the critical domain gap between aerial and ground data.
Reconstructing 3D scenes from a single view gets a boost by explicitly recognizing and leveraging repeated object instances, like chairs and tables, to inform and refine the reconstruction.
