Research map / Image generation / Autoregressive and latent generation
Lending Orientation to Neural Networks for Cross-View Geo-Localization
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Measured effects reported in the paper
| What was changed | Where | Measured | Effect |
|---|---|---|---|
| Add per-pixel orientation maps to RGB input (ablation) | 7-layer Siamese network · CVUSA test | r@1: 9.83 -> 31.71 | Helped |
| Add per-pixel orientation maps to RGB input (ablation) | 7-layer Siamese network · CVUSA test | r@top 1%: 68.61 -> 93.19 | Helped |
| Inject orientation maps at every convolutional layer rather than only at the input (ablation) | 7-layer Siamese network · CVUSA test | r@top 1%: 93.19 -> 93.15 | No clear effect |
| Use a 16-layer VGG with orientation maps instead of the 7-layer network (ablation) | Cross-view localization · CVUSA test | r@top 1%: 93.19 -> 93.91 | Helped |
| Increase error in estimated north orientation (ablation) | Proposed method · CVUSA test | recall | Hurt |
| Use the proposed method rather than CVM-net | Cross-view localization · CVUSA test | r@1: 18.80 -> 31.71 | Helped |
| Use the proposed method rather than CVM-net | Cross-view localization · CVUSA test | r@top 1%: 91.54 -> 93.19 | Helped |
| Use the proposed method rather than the compared method | Cross-view localization · CVACT test | recall@1: +15.84% | Helped |
Closest papers by meaning
- From Coarse to Fine: A Matching and Alignment Framework for Unsupervised Cross-View Geo-Localization (AAAI 2025 · similarity 0.91)
- Aligning Geometric Spatial Layout in Cross-View Geo-Localization via Feature Recombination (AAAI 2024 · similarity 0.90)
- GeoRanker: Distance-Aware Ranking for Worldwide Image Geolocalization (NeurIPS 2025 · similarity 0.88)
- Unleashing Unlabeled Data: A Paradigm for Cross-View Geo-Localization (CVPR 2024 · similarity 0.88)
- Scaling Image Geo-Localization to Continent Level (NeurIPS 2025 · similarity 0.88)
- View From Above: Orthogonal-View aware Cross-view Localization (CVPR 2024 · similarity 0.87)
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