mlsanityData to 7 Oct 2026

PointLoc: Deep Pose Regressor for LiDAR Point Cloud Localization

arXiv 2003.02392 ↗First posted 5 Mar 2020cs.ROcited by 25

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Abstract (arXiv)

In this paper, we present a novel end-to-end learning-based LiDAR relocalization framework, termed PointLoc, which infers 6-DoF poses directly using only a single point cloud as input, without requiring a pre-built map. Compared to RGB image-based relocalization, LiDAR frames can provide rich and robust geometric information about a scene. However, LiDAR point clouds are unordered and unstructured making it difficult to apply traditional deep learning regression models for this task. We address this issue by proposing a novel PointNet-style architecture with self-attention to efficiently estimate 6-DoF poses from 360deg LiDAR input frames.Extensive experiments on recently released challenging Oxford Radar RobotCar dataset and real-world robot experiments demonstrate that the proposedmethod can achieve accurate relocalization performance.

Key facts. Cited by 25 papers in the map (data through 7 Oct 2026). First posted on arXiv 5 Mar 2020.

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2021: 2; 2022: 1; 2023: 5; 2024: 1; 2025: 7; 2026: 9.

25 papers.

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  1. 2021NDT-Transformer: Large-Scale 3D Point Cloud Localisation using the Normal Distribution Transform Representationcited by 38
  2. 2023HypLiLoc: Towards Effective LiDAR Pose Regression with Hyperbolic Fusioncited by 24
  3. 2022RobustLoc: Robust Camera Pose Regression in Challenging Driving Environmentscited by 18
  4. 2025LightLoc: Learning Outdoor LiDAR Localization at Light Speedcited by 10
  5. 2021RadarLoc: Learning to Relocalize in FMCW Radarcited by 5
  6. 2025PRISM-DP: Spatial Pose-based Observations for Diffusion-Policies via Segmentation, Mesh Generation, and Pose Trackingcited by 5
  7. 2023TransFusionOdom: Interpretable Transformer-based LiDAR-Inertial Fusion Odometry Estimationcited by 4
  8. 2024FlashMix: Fast Map-Free LiDAR Localization via Feature Mixing and Contrastive-Constrained Accelerated Trainingcited by 3
  9. 2023Slice Transformer and Self-supervised Learning for 6DoF Localization in 3D Point Cloud Mapscited by 2
  10. 2023FusionLoc: Camera-2D LiDAR Fusion Using Multi-Head Self-Attention for End-to-End Serving Robot Relocalizationcited by 2
  11. 2025BEVDiffLoc: End-to-End LiDAR Global Localization in BEV View based on Diffusion Modelcited by 2
  12. 2023UnLoc: A Universal Localization Method for Autonomous Vehicles using LiDAR, Radar and/or Camera Inputcited by 1
13 more
  1. 2025Localization Meets Uncertainty: Uncertainty-Aware Multi-Modal Localizationcited by 1
  2. 2025V2VLoc: Robust GNSS-Free Collaborative Perception via LiDAR Localizationcited by 1
  3. 2026LEADER: Learning Reliable Local-to-Global Correspondences for LiDAR Relocalizationcited by 1
  4. 2025Diffusion Based Robust LiDAR Place Recognitioncited by 0
  5. 2025ThermalLoc: A Vision Transformer-Based Approach for Robust Thermal Camera Relocalization in Large-Scale Environmentscited by 0
  6. 2026From Single Scan to Sequential Consistency: A New Paradigm for LIDAR Relocalizationcited by 0
  7. 2026SOAR: Regression-based LiDAR Relocalization for UAVscited by 0
  8. 2026MB-Loc: Multi-planar Bird's-eye-view Localization in outdoor LiDAR scenescited by 0
  9. 2026Learning 1-Bit LiDAR-based Localization with Auxiliary Objectivecited by 0
  10. 2026UQ-Loc: Uncertainty-Aware LiDAR Scene Coordinate Regressioncited by 0
  11. 2026LightLoc++: Sensor-Robust Representation Learning for Efficient Outdoor LiDAR Localizationcited by 0
  12. 2026ReLoc: Rethinking Scene Coordinate Regression Architecture for Robust Outdoor LiDAR-based Localizationcited by 0
  13. 2026Temporal-Aware Fusion for Robust Outdoor LiDAR Localizationcited by 0