A learned end-to-end differentiable method for hierarchical scene graph matching outperforms combinatorial baselines in F1 score and speed for BIM-assisted robot localization, with zero-shot generalization from floor-plan training to real LiDAR data.
Learning combinatorial embedding networks for deep graph matching,
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Learning-Based Hierarchical Scene Graph Matching for Robot Localization Leveraging Prior Maps
A learned end-to-end differentiable method for hierarchical scene graph matching outperforms combinatorial baselines in F1 score and speed for BIM-assisted robot localization, with zero-shot generalization from floor-plan training to real LiDAR data.