HyperAI
Home
News
Latest Papers
Tutorials
Datasets
Wiki
SOTA
LLM Models
GPU Leaderboard
Events
Search
About
English
HyperAI
Toggle sidebar
Search the site…
⌘
K
Home
SOTA
Drone View Target Localization
Drone View Target Localization On University 1
Drone View Target Localization On University 1
Metrics
AP
Recall@1
Results
Performance results of various models on this benchmark
Columns
Model Name
AP
Recall@1
Paper Title
Repository
FSRA
84.82
82.25
A Transformer-Based Feature Segmentation and Region Alignment Method For UAV-View Geo-Localization
RK-Net
70.23
66.13
Joint Representation Learning and Keypoint Detection for Cross-view Geo-localization
CV-Cities
95.01
97.43
CV-Cities: Advancing Cross-View Geo-Localization in Global Cities
Instance Loss
63.13
58.49
University-1652: A Multi-view Multi-source Benchmark for Drone-based Geo-localization
Cross-view Consistent Attention
93.31
91.57
A Novel Geo-Localization Method for UAV and Satellite Images Using Cross-View Consistent Attention
GNN-Reranking
74.11
70.3
Understanding Image Retrieval Re-Ranking: A Graph Neural Network Perspective
LPN + USAM
80.55
77.60
Joint Representation Learning and Keypoint Detection for Cross-view Geo-localization
Sample4Geo
93.81
92.65
Sample4Geo: Hard Negative Sampling For Cross-View Geo-Localisation
LPN
79.14
75.93
Each Part Matters: Local Patterns Facilitate Cross-view Geo-localization
Orientation-Guided Sample4Geo
96.88
96.13
Orientation-Guided Contrastive Learning for UAV-View Geo-Localisation
-
SAFA + USAM
75.79
72.19
Joint Representation Learning and Keypoint Detection for Cross-view Geo-localization
0 of 11 row(s) selected.
Previous
Next