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Found 2 papers, 1 papers with code
I2P-Rec: Recognizing Images on Large-scale Point Cloud Maps through Bird's Eye View Projections
The experimental results evaluated on the KITTI dataset show that, with only a small set of training data, I2P-Rec achieves recall rates at Top-1\% over 80\% and 90\%, when localizing monocular and stereo images on point cloud maps, respectively.
BEVPlace: Learning LiDAR-based Place Recognition using Bird's Eye View Images
The experiments conducted on large-scale public datasets show that our method 1) achieves state-of-the-art performance in terms of recall rates, 2) is robust to view changes, 3) shows strong generalization ability, and 4) can estimate the positions of query point clouds.
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