8 papers
G2IA: Geometry-Guided Instance-Aware Retrieval and Refinement for Cross-Modal Place Recognition
Xianyun Jiao, Jingyi Xu, Zhongmiao Yan +2
Cross-modal place recognition (CMPR) enables camera-only robots to localize against pre-built LiDAR maps in autonomous navigation scenarios. This image-to-point-cloud setting is ch…
ParkingTransformer: LLM-Enhanced End-to-End Trajectory Planning for Autonomous Parking
Hauteng Wu, Xu Li, Dong Kong +4
End-to-end autonomous parking has emerged as a critical task within the realm of autonomous driving. However, existing methods suffer from black-box characteristics, lacking high-l…
SinGeo: Unlock Single Model's Potential for Robust Cross-View Geo-Localization
Yang Chen, Xieyuanli Chen, Junxiang Li +2
Robust cross-view geo-localization (CVGL) remains challenging despite the surge in recent progress. Existing methods still rely on field-of-view (FoV)-specific training paradigms,…
TOL: Textual Localization with OpenStreetMap
Youqi Liao, Shuhao Kang, Jingyu Xu +6
Natural language provides an intuitive way to express spatial intent in geospatial applications. While existing localization methods often rely on dense point cloud maps or high-re…
MPTF-Net: Multi-view Pyramid Transformer Fusion Network for LiDAR-based Place Recognition
Shuyuan Li, Zihang Wang, Xieyuanli Chen +5
LiDAR-based place recognition (LPR) is essential for global localization and loop-closure detection in large-scale SLAM systems. Existing methods typically construct global descrip…
VLM-Loc: Localization in Point Cloud Maps via Vision-Language Models
Shuhao Kang, Youqi Liao, Peijie Wang +5
Text-to-point-cloud (T2P) localization aims to infer precise spatial positions within 3D point cloud maps from natural language descriptions, reflecting how humans perceive and com…