# LCPR: A Multi-Scale Attention-Based LiDAR-Camera Fusion Network for Place Recognition

arXiv: https://arxiv.org/abs/2311.03198 · HTML: https://mlsanity.com/paper/2311.03198/

## Key facts

- Cited by 17 papers in the map (data through 14 Oct 2026).
- Builds on 27 of its 44 references that are in the map.
- First posted on arXiv 6 Nov 2023.

## Builds on (most cited first, 27 of 27)

- [Attention Is All You Need](https://mlsanity.com/paper/1706.03762/) (2017)
- [Deep Residual Learning for Image Recognition](https://mlsanity.com/paper/1512.03385/) (2015)
- [PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation](https://mlsanity.com/paper/1612.00593/) (2016)
- [nuScenes: A multimodal dataset for autonomous driving](https://mlsanity.com/paper/1903.11027/) (2019)
- [Billion-scale similarity search with GPUs](https://mlsanity.com/paper/1702.08734/) (2017)
- [NetVLAD: CNN architecture for weakly supervised place recognition](https://mlsanity.com/paper/1511.07247/) (2015)
- [BEVFusion: Multi-Task Multi-Sensor Fusion with Unified Bird's-Eye View Representation](https://mlsanity.com/paper/2205.13542/) (2022)
- [Fine-tuning CNN Image Retrieval with No Human Annotation](https://mlsanity.com/paper/1711.02512/) (2017)
- [PointPainting: Sequential Fusion for 3D Object Detection](https://mlsanity.com/paper/1911.10150/) (2019)
- [Multi-Modal Fusion Transformer for End-to-End Autonomous Driving](https://mlsanity.com/paper/2104.09224/) (2021)
- [Patch-NetVLAD: Multi-Scale Fusion of Locally-Global Descriptors for Place Recognition](https://mlsanity.com/paper/2103.01486/) (2021)
- [PointNetVLAD: Deep Point Cloud Based Retrieval for Large-Scale Place Recognition](https://mlsanity.com/paper/1804.03492/) (2018)
- [MinkLoc3D: Point Cloud Based Large-Scale Place Recognition](https://mlsanity.com/paper/2011.04530/) (2020)
- [OverlapTransformer: An Efficient and Rotation-Invariant Transformer Network for LiDAR-Based Place Recognition](https://mlsanity.com/paper/2203.03397/) (2022)
- [PCAN: 3D Attention Map Learning Using Contextual Information for Point Cloud Based Retrieval](https://mlsanity.com/paper/1904.09793/) (2019)
- [MinkLoc++: Lidar and Monocular Image Fusion for Place Recognition](https://mlsanity.com/paper/2104.05327/) (2021)
- [AdaFusion: Visual-LiDAR Fusion with Adaptive Weights for Place Recognition](https://mlsanity.com/paper/2111.11739/) (2021)
- [Convolutional Neural Network-based Place Recognition](https://mlsanity.com/paper/1411.1509/) (2014)
- [MatrixVT: Efficient Multi-Camera to BEV Transformation for 3D Perception](https://mlsanity.com/paper/2211.10593/) (2022)
- [SeqOT: A Spatial-Temporal Transformer Network for Place Recognition Using Sequential LiDAR Data](https://mlsanity.com/paper/2209.07951/) (2022)
- [CVTNet: A Cross-View Transformer Network for Place Recognition Using LiDAR Data](https://mlsanity.com/paper/2302.01665/) (2023)
- [CORAL: Colored structural representation for bi-modal place recognition](https://mlsanity.com/paper/2011.10934/) (2020)
- [PIC-Net: Point Cloud and Image Collaboration Network for Large-Scale Place Recognition](https://mlsanity.com/paper/2008.00658/) (2020)
- [AutoPlace: Robust Place Recognition with Single-chip Automotive Radar](https://mlsanity.com/paper/2109.08652/) (2021)
- [An Efficient and Scalable Collection of Fly-inspired Voting Units for Visual Place Recognition in Changing Environments](https://mlsanity.com/paper/2109.10986/) (2021)
- [General Place Recognition Survey: Towards the Real-world Autonomy Age](https://mlsanity.com/paper/2209.04497/) (2022)
- [CAMAL: Context-Aware Multi-layer Attention framework for Lightweight Environment Invariant Visual Place Recognition](https://mlsanity.com/paper/1909.08153/) (2019)

## Built on by (most cited first, 17 of 17)

- [UAVScenes: A Multi-Modal Dataset for UAVs](https://mlsanity.com/paper/2507.22412/) (2025)
- [GSPR: Multimodal Place Recognition Using 3D Gaussian Splatting for Autonomous Driving](https://mlsanity.com/paper/2410.00299/) (2024)
- [SegLocNet: Multimodal Localization Network for Autonomous Driving via Bird's-Eye-View Segmentation](https://mlsanity.com/paper/2502.20077/) (2025)
- [Explicit Interaction for Fusion-Based Place Recognition](https://mlsanity.com/paper/2402.17264/) (2024)
- [VGGT-MPR: VGGT-Enhanced Multimodal Place Recognition in Autonomous Driving Environments](https://mlsanity.com/paper/2602.19735/) (2026)
- [BEV2PR: BEV-Enhanced Visual Place Recognition with Structural Cues](https://mlsanity.com/paper/2403.06600/) (2024)
- [LRFusionPR: A Polar BEV-Based LiDAR-Radar Fusion Network for Place Recognition](https://mlsanity.com/paper/2504.19186/) (2025)
- [PRFusion: Toward Effective and Robust Multi-Modal Place Recognition with Image and Point Cloud Fusion](https://mlsanity.com/paper/2410.04939/) (2024)
- [UniMPR: A Unified Framework for Multimodal Place Recognition with Heterogeneous Sensor Configurations](https://mlsanity.com/paper/2512.18279/) (2025)
- [LaVPR: Benchmarking Language and Vision for Place Recognition](https://mlsanity.com/paper/2602.03253/) (2026)
- [HypeVPR: Exploring Hyperbolic Space for Perspective to Equirectangular Visual Place Recognition](https://mlsanity.com/paper/2506.04764/) (2025)
- [Towards classification-based representation learning for place recognition on LiDAR scans](https://mlsanity.com/paper/2511.00738/) (2025)
- [(MGS)2-Net: Unifying Micro-Geometric Scale and Macro-Geometric Structure for Cross-View Geo-Localization](https://mlsanity.com/paper/2602.10704/) (2026)
- [MPTF-Net: Multi-view Pyramid Transformer Fusion Network for LiDAR-based Place Recognition](https://mlsanity.com/paper/2604.04513/) (2026)
- [MAG-VLAQ: Multi-modal Aerial-Ground Query Aggregation for Cross-View Place Recognition](https://mlsanity.com/paper/2605.09418/) (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)
- [G2IA: Geometry-Guided Instance-Aware Retrieval and Refinement for Cross-Modal Place Recognition](https://mlsanity.com/paper/2606.15287/) (2026)

## Abstract (arXiv)

Place recognition is one of the most crucial modules for autonomous vehicles to identify places that were previously visited in GPS-invalid environments. Sensor fusion is considered an effective method to overcome the weaknesses of individual sensors. In recent years, multimodal place recognition fusing information from multiple sensors has gathered increasing attention. However, most existing multimodal place recognition methods only use limited field-of-view camera images, which leads to an imbalance between features from different modalities and limits the effectiveness of sensor fusion. In this paper, we present a novel neural network named LCPR for robust multimodal place recognition, which fuses LiDAR point clouds with multi-view RGB images to generate discriminative and yaw-rotation invariant representations of the environment. A multi-scale attention-based fusion module is proposed to fully exploit the panoramic views from different modalities of the environment and their correlations. We evaluate our method on the nuScenes dataset, and the experimental results show that our method can effectively utilize multi-view camera and LiDAR data to improve the place recognition performance while maintaining strong robustness to viewpoint changes. Our open-source code and pre-trained models are available at https://github.com/ZhouZijie77/LCPR .