Visual Localization On Aachen Day Night V1 1
Metrics
Results
Performance results of various models on this benchmark
| Paper Title | ||||
|---|---|---|---|---|
| GIM-LoFTR | 79.1 | 91.6 | 100.0 | GIM: Learning Generalizable Image Matcher From Internet Videos |
| LoFTR | 78.5 | 90.6 | 99.0 | LoFTR: Detector-Free Local Feature Matching with Transformers |
| GIM-SuperGlue | 78.0 | 90.6 | 100.0 | GIM: Learning Generalizable Image Matcher From Internet Videos |
| GIM-DKM | 77.0 | 90.1 | 99.5 | GIM: Learning Generalizable Image Matcher From Internet Videos |
| SuperGlue | 77.0 | 90.6 | 100.0 | SuperGlue: Learning Feature Matching with Graph Neural Networks |
| SCFeat | 74.3 | 89 | 98.4 | Shared Coupling-bridge for Weakly Supervised Local Feature Learning |
| DKM | 70.2 | 90.1 | 97.4 | DKM: Dense Kernelized Feature Matching for Geometry Estimation |
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