# UniLoc: Towards Universal Place Recognition Using Any Single Modality

arXiv: https://arxiv.org/abs/2412.12079 · HTML: https://mlsanity.com/paper/2412.12079/

## Key facts

- Cited by 10 papers in the map (data through 14 Oct 2026).
- Builds on 3 of its 45 references that are in the map.
- First posted on arXiv 16 Dec 2024.

## Builds on (most cited first, 3 of 3)

- [DINO: DETR with Improved DeNoising Anchor Boxes for End-to-End Object Detection](https://mlsanity.com/paper/2203.03605/) (2022)
- [Text to Point Cloud Localization with Relation-Enhanced Transformer](https://mlsanity.com/paper/2301.05372/) (2023)
- [CVTNet: A Cross-View Transformer Network for Place Recognition Using LiDAR Data](https://mlsanity.com/paper/2302.01665/) (2023)

## Built on by (most cited first, 10 of 10)

- [AnyThermal: Towards Learning Universal Representations for Thermal Perception](https://mlsanity.com/paper/2602.06203/) (2026)
- [VGGT-MPR: VGGT-Enhanced Multimodal Place Recognition in Autonomous Driving Environments](https://mlsanity.com/paper/2602.19735/) (2026)
- [L2RSI: Cross-view LiDAR-based Place Recognition for Large-scale Urban Scenes via Remote Sensing Imagery](https://mlsanity.com/paper/2503.11245/) (2025)
- [HCCM: Hierarchical Cross-Granularity Contrastive and Matching Learning for Natural Language-Guided Drones](https://mlsanity.com/paper/2508.21539/) (2025)
- [SGLoc: Semantic Localization System for Camera Pose Estimation from 3D Gaussian Splatting Representation](https://mlsanity.com/paper/2507.12027/) (2025)
- [Text2Loc++: Generalizing 3D Point Cloud Localization from Natural Language](https://mlsanity.com/paper/2511.15308/) (2025)
- [MAG-VLAQ: Multi-modal Aerial-Ground Query Aggregation for Cross-View Place Recognition](https://mlsanity.com/paper/2605.09418/) (2026)
- [G2IA: Geometry-Guided Instance-Aware Retrieval and Refinement for Cross-Modal Place Recognition](https://mlsanity.com/paper/2606.15287/) (2026)
- [GRASP: Granularity-Aware Region Alignment and Semantic Prototype Learning for Fine-Grained Cross-Modal Understanding in Drone Views](https://mlsanity.com/paper/2608.09270/) (2026)
- [GeoUniPR: A Geometry-Consistent Unified Framework for Cross-Modal Place Recognition](https://mlsanity.com/paper/2608.11263/) (2026)

## Abstract (arXiv)

To date, most place recognition methods focus on single-modality retrieval. While they perform well in specific environments, cross-modal methods offer greater flexibility by allowing seamless switching between map and query sources. It also promises to reduce computation requirements by having a unified model, and achieving greater sample efficiency by sharing parameters. In this work, we develop a universal solution to place recognition, UniLoc, that works with any single query modality (natural language, image, or point cloud). UniLoc leverages recent advances in large-scale contrastive learning, and learns by matching hierarchically at two levels: instance-level matching and scene-level matching. Specifically, we propose a novel Self-Attention based Pooling (SAP) module to evaluate the importance of instance descriptors when aggregated into a place-level descriptor. Experiments on the KITTI-360 dataset demonstrate the benefits of cross-modality for place recognition, achieving superior performance in cross-modal settings and competitive results also for uni-modal scenarios. Our project page is publicly available at https://yan-xia.github.io/projects/UniLoc/.