4 papers
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…
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…
Aerial-ground Cross-modal Localization: Dataset, Ground-truth, and Benchmark
Yandi Yang, Jianping Li, Youqi Liao +5
Accurate visual localization in dense urban environments poses a fundamental task in photogrammetry, geospatial information science, and robotics. While imagery is a low-cost and w…
OSMLoc: Single Image-Based Visual Localization in OpenStreetMap with Fused Geometric and Semantic Guidance
Youqi Liao, Xieyuanli Chen, Shuhao Kang +4
OpenStreetMap (OSM), a rich and versatile source of volunteered geographic information (VGI), facilitates human self-localization and scene understanding by integrating nearby visu…