# HeLiPR: Heterogeneous LiDAR Dataset for inter-LiDAR Place Recognition under Spatiotemporal Variations

arXiv: https://arxiv.org/abs/2309.14590 · HTML: https://mlsanity.com/paper/2309.14590/

## Key facts

- Cited by 27 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 26 Sep 2023.

## Built on by (most cited first, 27 of 27)

- [Register Any Point: Scaling 3D Point Cloud Registration by Flow Matching](https://mlsanity.com/paper/2512.01850/) (2025)
- [HeLiMOS: A Dataset for Moving Object Segmentation in 3D Point Clouds From Heterogeneous LiDAR Sensors](https://mlsanity.com/paper/2408.06328/) (2024)
- [LifelongPR: Lifelong point cloud place recognition based on sample replay and prompt learning](https://mlsanity.com/paper/2507.10034/) (2025)
- [Polar Perspectives: Evaluating 2-D LiDAR Projections for Robust Place Recognition with Visual Foundation Models](https://mlsanity.com/paper/2512.02897/) (2025)
- [FMCW-LIO: A Doppler LiDAR-Inertial Odometry](https://mlsanity.com/paper/2609.29374/) (2026)
- [POD: Predictive Object Detection with Single-Frame FMCW LiDAR Point Cloud](https://mlsanity.com/paper/2504.05649/) (2025)
- [RE-TRIP : Reflectivity Instance Augmented Triangle Descriptor for 3D Place Recognition](https://mlsanity.com/paper/2505.16165/) (2025)
- [Toward Zero-Shot Point Cloud Registration Across Diverse Scales, Scenes, and Sensor Setups](https://mlsanity.com/paper/2601.02759/) (2026)
- [TreeLoc: 6-DoF LiDAR Global Localization in Forests via Inter-Tree Geometric Matching](https://mlsanity.com/paper/2602.01501/) (2026)
- [PROBE: Probabilistic Occupancy BEV Encoding with Analytical Translation Robustness for 3D Place Recognition](https://mlsanity.com/paper/2603.05965/) (2026)
- [Moving Object Segmentation in Point Cloud Data using Hidden Markov Models](https://mlsanity.com/paper/2410.18638/) (2024)
- [Wireless Communication as an Information Sensor for Multi-agent Cooperative Perception: A Survey](https://mlsanity.com/paper/2505.00747/) (2025)
- [The City that Never Settles: Simulation-based LiDAR Dataset for Long-Term Place Recognition Under Extreme Structural Changes](https://mlsanity.com/paper/2505.05076/) (2025)
- [GroundLoc: Efficient Large-Scale Outdoor LiDAR-Only Localization](https://mlsanity.com/paper/2510.24623/) (2025)
- [Calibrated Keyframe-Segment Selection for Descriptor-Agnostic LiDAR Loop Closure in Repetitive Environments](https://mlsanity.com/paper/2512.09447/) (2025)
- [WHU-PCPR: A cross-platform heterogeneous point cloud dataset for place recognition in complex urban scenes](https://mlsanity.com/paper/2601.06442/) (2026)
- [Loop Closure via Maximal Cliques in 3D LiDAR-Based SLAM](https://mlsanity.com/paper/2603.05397/) (2026)
- [Heterogeneous LiDAR Early Fusion and Learned Re-Ranking Strategy for Robust Long-Term Place Recognition in Unstructured Environments](https://mlsanity.com/paper/2606.13503/) (2026)
- [PROBE-X: Learning-Free Cross-FOV Place Recognition](https://mlsanity.com/paper/2607.06782/) (2026)
- [InLiER: Learning-Free Heterogeneous LiDAR Place Recognition via Intermediate Mixed-Radix Structural Keypoint Tokenization](https://mlsanity.com/paper/2607.16862/) (2026)
- [Accelerating Large-scale Bundle Adjustment for LiDAR Mapping via Parallel Computing](https://mlsanity.com/paper/2608.14266/) (2026)
- [LightLoc++: Sensor-Robust Representation Learning for Efficient Outdoor LiDAR Localization](https://mlsanity.com/paper/2608.15317/) (2026)
- [LF-GICP: Parameter-Free Degeneracy-Aware LiDAR Odometry via a Voxel-Normal Localizability Field](https://mlsanity.com/paper/2608.19522/) (2026)
- [DXPR: Depth-Based Vision-LiDAR Cross-Modal Place Recognition Using Vision Foundation Models](https://mlsanity.com/paper/2609.09005/) (2026)
- [Free-Init: Scan-Free, Motion-Free, and Correspondence-Free Initialization for Doppler LiDAR-Inertial Systems](https://mlsanity.com/paper/2609.29375/) (2026)
- [AevaScenes: An FMCW LiDAR Dataset and Benchmark for Long-Range Perception](https://mlsanity.com/paper/2609.33230/) (2026)
- [ROSETTA: Rotation Subspace Estimation for Training-free Transmodal Alignment](https://mlsanity.com/paper/2610.12871/) (2026)

## Abstract (arXiv)

Place recognition is crucial for robot localization and loop closure in simultaneous localization and mapping (SLAM). Light Detection and Ranging (LiDAR), known for its robust sensing capabilities and measurement consistency even in varying illumination conditions, has become pivotal in various fields, surpassing traditional imaging sensors in certain applications. Among various types of LiDAR, spinning LiDARs are widely used, while non-repetitive scanning patterns have recently been utilized in robotics applications. Some LiDARs provide additional measurements such as reflectivity, Near Infrared (NIR), and velocity from Frequency modulated continuous wave (FMCW) LiDARs. Despite these advances, there is a lack of comprehensive datasets reflecting the broad spectrum of LiDAR configurations for place recognition. To tackle this issue, our paper proposes the HeLiPR dataset, curated especially for place recognition with heterogeneous LiDARs, embodying spatiotemporal variations. To the best of our knowledge, the HeLiPR dataset is the first heterogeneous LiDAR dataset supporting inter-LiDAR place recognition with both non-repetitive and spinning LiDARs, accommodating different field of view (FOV)s and varying numbers of rays. The dataset covers diverse environments, from urban cityscapes to high-dynamic freeways, over a month, enhancing adaptability and robustness across scenarios. Notably, HeLiPR includes trajectories parallel to MulRan sequences, making it valuable for research in heterogeneous LiDAR place recognition and long-term studies. The dataset is accessible at https://sites.google.com/view/heliprdataset.