mlsanityData to 14 Oct 2026

OREOS: Oriented Recognition of 3D Point Clouds in Outdoor Scenarios

arXiv 1903.07918 ↗First posted 19 Mar 2019cs.ROcited by 13

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Abstract (arXiv)

We introduce a novel method for oriented place recognition with 3D LiDAR scans. A Convolutional Neural Network is trained to extract compact descriptors from single 3D LiDAR scans. These can be used both to retrieve near-by place candidates from a map, and to estimate the yaw discrepancy needed for bootstrapping local registration methods. We employ a triplet loss function for training and use a hard-negative mining strategy to further increase the performance of our descriptor extractor. In an evaluation on the NCLT and KITTI datasets, we demonstrate that our method outperforms related state-of-the-art approaches based on both data-driven and handcrafted data representation in challenging long-term outdoor conditions.

Key facts. Cited by 13 papers in the map (data through 14 Oct 2026). First posted on arXiv 19 Mar 2019.

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Citing papers per year: 2021: 5; 2022: 2; 2023: 1; 2024: 4; 2025: 1.

13 papers.

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  1. 2021LCDNet: Deep Loop Closure Detection and Point Cloud Registration for LiDAR SLAMcited by 67
  2. 2021EgoNN: Egocentric Neural Network for Point Cloud Based 6DoF Relocalization at the City Scalecited by 25
  3. 2021SSC: Semantic Scan Context for Large-Scale Place Recognitioncited by 24
  4. 2022InCloud: Incremental Learning for Point Cloud Place Recognitioncited by 22
  5. 2021Place recognition survey: An update on deep learning approachescited by 13
  6. 2021AttDLNet: Attention-based DL Network for 3D LiDAR Place Recognitioncited by 10
  7. 2023FRAME: Fast and Robust Autonomous 3D point cloud Map-merging for Egocentric multi-robot explorationcited by 6
  8. 2024RecNet: An Invertible Point Cloud Encoding through Range Image Embeddings for Multi-Robot Map Sharing and Reconstructioncited by 6
  9. 2024FRAME: A Modular Framework for Autonomous Map Merging: Advancements in the Fieldcited by 4
  10. 2022Translation Invariant Global Estimation of Heading Angle Using Sinogram of LiDAR Point Cloudcited by 3
  11. 2025LifelongPR: Lifelong point cloud place recognition based on sample replay and prompt learningcited by 2
  12. 2024An experimental evaluation of Siamese Neural Networks for robot localization using omnidirectional imaging in indoor environmentscited by 0
1 more
  1. 2024Why Sample Space Matters: Keyframe Sampling Optimization for LiDAR-based Place Recognitioncited by 0