arXiv (All)
open access
Learning Holistic Scene Layout against View Shifts in Cross-View Geo-Localization
Cross-view geo-localization remains challenging due to drastic appearance variations and geometric distortions caused by viewpoint changes. Existing methods primarily rely on discriminative feature learning or explicit geometric alignment, yet often overlook an important observation: humans tend to
Conceptio Open Archive
Analyze & explore related research in Conceptio
Connect this record directly into your research workflow or AI agent. Explore citations across open repositories, query full text, and export structured proof bundles.
This document is indexed with metadata only: full text is not available in the archive for this record. Open the official source ↗
Related documents
- Recurrent Cross-View Object Geo-Localization#612827
- Recurrent Cross-View Object Geo-Localization#611350
- GeoLink: A 3D-aware Framework to Improve Generalization for Cross-view Geo-localization#665710
- GeoLink: A 3D-aware Framework to Improve Generalization for Cross-view Geo-localization#664210
- A Unified Hierarchical Framework for Fine-grained Cross-view Geo-localization over Large-scale Scenarios#1012017
Record · ID 1297905
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Bring this data into your agent: Connect via MCP or API · 20 free credits to start · no card required
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive