SeqLoc: Beyond the Single Frame for Cross-View Geo-Localization in Feature-Sparse Scenes
Cross-View Geo-Localization (CVGL) with OpenStreetMap (OSM) performs well in structure-rich urban environments but collapses in feature-sparse scenes such as rural roads. To study this failure mode, in this work, we introduce CV-FSS, a benchmark that pairs sequential panoramas from five rural regions with aligned OSM maps, on which single-frame methods degrade drastically. We then propose SeqLoc, an online test-time sequence aggregation mechanism that recursively maintains a log-belief volume with three key components: (1) Entropy-Tempered Uncertainty (ETU) tempers each incoming pose likelihood volume by its normalized entropy; (2) Map-Guided Relocalization (MGR) mixes a map-shaped recove...
| Authors | Junwei Zheng, Yun Huang, Ruize Dai et al. |
|---|---|
| Primary category | cs.CV |
| Published | 8 August 2026 |
| Last updated at source | 11 August 2026 |
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