mlsanityData to 7 Oct 2026

LiteVLoc: Map-Lite Visual Localization for Image Goal Navigation

arXiv 2410.04419 ↗First posted 6 Oct 2024cs.RO cs.CVcited by 4

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Abstract (arXiv)

This paper presents LiteVLoc, a hierarchical visual localization framework that uses a lightweight topo-metric map to represent the environment. The method consists of three sequential modules that estimate camera poses in a coarse-to-fine manner. Unlike mainstream approaches relying on detailed 3D representations, LiteVLoc reduces storage overhead by leveraging learning-based feature matching and geometric solvers for metric pose estimation. A novel dataset for the map-free relocalization task is also introduced. Extensive experiments including localization and navigation in both simulated and real-world scenarios have validate the system's performance and demonstrated its precision and efficiency for large-scale deployment. Code and data will be made publicly available.

Key facts. Cited by 4 papers in the map (data through 7 Oct 2026). Builds on 59 of its 85 references that are in the map. First posted on arXiv 6 Oct 2024.

Builds on

59 of 85 references.

References · 59

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38 more
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50 most cited of 59 All 59 (JSON)

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2025: 2; 2026: 2.

4 papers.

  1. 2025Watch Your STEPP: Semantic Traversability Estimation using Pose Projected Featurescited by 4
  2. 2026360CityArena: A Realistic Virtual Urban Navigation Benchmark for Embodied Agentscited by 1
  3. 2025DCReg: Decoupled Characterization for Efficient Degenerate LiDAR Registrationcited by 0
  4. 2026OpenNavMap: Multi-Session Appearance-Based Topometric Mapping for Scalable Visual Navigationcited by 0