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GeoGraph: Graph-based multi-view object detection with geometric cues end-to-end
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.
GeoGraph: Learning graph-based multi-view object detection with geometric cues end-to-end
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.
Simultaneous multi-view instance detection with learned geometric soft-constraints
We propose to jointly learn multi-view geometry and warping between views of the same object instances for robust cross-view object detection.
Towards seamless multi-view scene analysis from satellite to street-level
In this paper, we discuss and review how combined multi-view imagery from satellite to street-level can benefit scene analysis.
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