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Drone Navigation On University 1652 1
评估指标
AP
Recall@1
评测结果
各个模型在此基准测试上的表现结果
| Paper Title | Repository | |||
|---|---|---|---|---|
| FSRA | 81.53 | 87.87 | A Transformer-Based Feature Segmentation and Region Alignment Method For UAV-View Geo-Localization | |
| LPN + USAM | 75.96 | 86.59 | Joint Representation Learning and Keypoint Detection for Cross-view Geo-localization | - |
| LPN | 74.79 | 86.45 | Each Part Matters: Local Patterns Facilitate Cross-view Geo-localization | |
| SAFA + USAM | 71.77 | 83.23 | Joint Representation Learning and Keypoint Detection for Cross-view Geo-localization | - |
| RK-Net | 65.76 | 80.17 | Joint Representation Learning and Keypoint Detection for Cross-view Geo-localization | - |
| Instance Loss | 58.74 | 71.18 | University-1652: A Multi-view Multi-source Benchmark for Drone-based Geo-localization |
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