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GeoGraph: Learning graph-based multi-view object detection with geometric cues end-to-end
[article]
2020
arXiv
pre-print
In this paper we propose an end-to-end learnable approach that detects static urban objects from multiple views, re-identifies instances, and finally assigns a geographic position per object. Our method relies on a Graph Neural Network (GNN) to, detect all objects and output their geographic positions given images and approximate camera poses as input. Our GNN simultaneously models relative pose and image evidence, and is further able to deal with an arbitrary number of input views. Our method
arXiv:2003.10151v2
fatcat:neleyzbkpfhylbrusf76el5yry