LangLoc: "Tell Me What You See"
We tackle fine-grained indoor localization from natural language: given a free-form description of one's surroundings, estimate the observer's 2D position and heading within a known 3D environment. Language queries are lightweight, privacy-preserving, and need no camera - yet prior work stops at coarse scene retrieval and cannot resolve an intra-scene pose. We close this gap with LangLoc, a three-stage pipeline that (i) retrieves the correct scene via a dual-branch GATv2 encoder with CLIP semantic features, surpassing the previous best by 8 percentage points in Top-1 recall; (ii) estimates position and heading by scoring a dense floor grid through ray-cast object visibility, reaching a me...
| Authors | Shaurya Kishore Panwar, Roham Zendehdel Nobari, Shirley Feng Yi Lau et al. |
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| Primary category | cs.CV |
| Published | 6 July 2026 |
| Last updated at source | 6 July 2026 |
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