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‎State-of-the-art/README.md‎

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|Instance Loss + Weighted Soft Margin Triplet Loss | 65.93 | 70.18 | 76.03 | 66.36|
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|RK-Net (USAM) | 66.13 | 70.23 | 80.17 | 65.76 | Lin J, Zheng Z, Zhong Z, Luo Z, Li S, Yang Y, Sebe N. Joint Representation Learning and Keypoint Detection for Cross-view Geo-localization. TIP 2022. [[Paper]](https://zhunzhong.site/paper/RK_Net.pdf) [[Code]](https://github.com/AggMan96/RK-Net) |
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|LCM (ResNet-50) | 66.65 | 70.82 | 79.89 |65.38 | Ding L, Zhou J, Meng L, et al. A Practical Cross-View Image Matching Method between UAV and Satellite for UAV-Based Geo-Localization[J]. Remote Sensing, 2021, 13(1): 47. [[Paper]](https://www.mdpi.com/2072-4292/13/1/47/pdf)|
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|DWDR | 69.77 | 73.73 | 81.46 | 70.45 | Tingyu W, Zhedong Z, Zunjie Z, Yuhan G, Yi Y, and Chenggang Y. "Learning Cross-view Geo-localization Embeddings via Dynamic Weighted Decorrelation Regularization" IEEE Transactions on Geoscience and Remote Sensing, 2024. [[Paper]](https://ieeexplore.ieee.org/document/10744586) |
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|DWDR | 69.77 | 73.73 | 81.46 | 70.45 | Tingyu W, Zhedong Z, Zunjie Z, Yuhan G, Yi Y, and Chenggang Y. "Learning Cross-view Geo-localization Embeddings via Dynamic Weighted Decorrelation Regularization" IEEE Transactions on Geoscience and Remote Sensing, 2024. [[Paper]](https://ieeexplore.ieee.org/document/10744586) [[Code]](https://github.com/wtyhub/DWDR) |
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|Instance Loss + GNN ReRanking |70.30| 74.11 | - | - | Zhang, Xuanmeng, Minyue Jiang, Zhedong Zheng, Xiao Tan, Errui Ding, and Yi Yang. "Understanding Image Retrieval Re-Ranking: A Graph Neural Network Perspective." arXiv 2020. [[Paper]](https://arxiv.org/abs/2012.07620)[[Code]](https://github.com/layumi/University1652-Baseline/tree/master/GPU-Re-Ranking)|
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|Instance Loss + USAM + SAFA | 72.19 | 75.79 | 83.23 | 71.77 |
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|MuSe-Net (Normal Weather) | 74.48 | 77.83 |88.02 | 75.10 | Wang T, Zheng Z, Sun Y, et al. Multiple-environment Self-adaptive Network for Aerial-view Geo-localization[J]. Pattern Recognition, 2024. [[Code]](https://github.com/wtyhub/MuseNet) |
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|SAIG-D| 78.85 | 81.62 | 86.45 | 78.48 | Yingying Zhu, Hongji Yang, Yuxin Lu and Qiang Huang. Simple, Effective and General: A New Backbone for Cross-view Image Geo-localization. ArXiv 2023|
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|LDRVSD| 78.66 | 81.55 | 89.30 | 79.17 | Qian Hu, Wansi Li, Xing Xu, Ning Liu, Lei Wang. Learning discriminative representations via variational self-distillation for cross-view geo-localization. Computers and Electrical Engineering 2022 [[Paper]](https://www.sciencedirect.com/science/article/pii/S0045790622005559) |
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|PCL | 79.47 | 83.63 | 87.69 | 78.51 | Xiaoyang Tian, Jie Shao, Deqiang Ouyang, and Heng Tao Shen. UAV-Satellite View Synthesis for Cross-view Geo-Localization. TCSVT 2021. [[Paper]](https://ieeexplore.ieee.org/document/9583266) |
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|LPN + DWDR | 81.51 | 84.11 | 88.30 | 79.38 | Tingyu W, Zhedong Z, Zunjie Z, Yuhan G, Yi Y, and Chenggang Y. "Learning Cross-view Geo-localization Embeddings via Dynamic Weighted Decorrelation Regularization" arXiv 2022. [[Paper]](https://arxiv.org/pdf/2211.05296.pdf) |
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|LPN + DWDR | 81.51 | 84.11 | 88.30 | 79.38 | Tingyu W, Zhedong Z, Zunjie Z, Yuhan G, Yi Y, and Chenggang Y. "Learning Cross-view Geo-localization Embeddings via Dynamic Weighted Decorrelation Regularization" IEEE Transactions on Geoscience and Remote Sensing, 2024. [[Paper]](https://ieeexplore.ieee.org/document/10744586) [[Code]](https://github.com/wtyhub/DWDR) |
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|FSRA (k=1)| 82.25 | 84.82 | 87.87 | 81.53 | Ming Dai, Jianhong Hu, Jiedong Zhuang, Enhui Zheng. A Transformer-Based Feature Segmentation and Region Alignment Method For UAV-View Geo-Localization. TCSVT 2022. [[Paper]](https://arxiv.org/pdf/2201.09206.pdf) [[Code]](https://github.com/dmmm1997/fsra) |
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|FSRA (k=3)| 84.51 | 86.71 | 88.45 | 83.37 |
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|TransFG| 84.01 | 86.31 | 90.16 | 84.61 | Zhao, H., Ren, K., Yue, T., Zhang, C., & Yuan, S. (2024). TransFG: A Cross-View Geo-Localization of Satellite and UAVs Imagery Pipeline Using Transformer-Based Feature Aggregation and Gradient Guidance. IEEE Transactions on Geoscience and Remote Sensing. |
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|PAAN | 84.51 | 86.78 | 91.01 | 82.28 | Duc Viet Bui, Masao Kubo, Hiroshi Sato. A Part-aware Attention Neural Network for Cross-view Geo-localization between UAV and Satellite. Journal of Robotics Networking and Artificial Life 2022 [[Paper]](https://www.researchgate.net/profile/Viet-Bui-9/publication/366091845_A_Part-aware_Attention_Neural_Network_for_Cross-view_Geo-localization_between_UAV_and_Satellite/links/63914181e42faa7e75a6122e/A-Part-aware-Attention-Neural-Network-for-Cross-view-Geo-localization-between-UAV-and-Satellite.pdf) |
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|Swin-B + DWDR | 86.41 | 88.41 | 91.30 | 86.02 | Tingyu W, Zhedong Z, Zunjie Z, Yuhan G, Yi Y, and Chenggang Y. "Learning Cross-view Geo-localization Embeddings via Dynamic Weighted Decorrelation Regularization" arXiv 2022. [[Paper]](https://arxiv.org/pdf/2211.05296.pdf) |
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|Swin-B + DWDR | 86.41 | 88.41 | 91.30 | 86.02 | Tingyu W, Zhedong Z, Zunjie Z, Yuhan G, Yi Y, and Chenggang Y. "Learning Cross-view Geo-localization Embeddings via Dynamic Weighted Decorrelation Regularization" IEEE Transactions on Geoscience and Remote Sensing, 2024. [[Paper]](https://ieeexplore.ieee.org/document/10744586) [[Code]](https://github.com/wtyhub/DWDR) |
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|MBF | 89.05 | 90.61 | 93.15| 88.17 | Runzhe Zhu , Mingze Yang , Ling Yin * , Fei Wu and Yuncheng Yang. "UAV’s Status Is Worth Considering: A Fusion Representations Matching Method for Geo-Localization" Sensors |
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|MCCG| 89.64 | 91.32 | 94.30 | 89.39 | Tianrui Shen, Yingmei Wei, Lai Kang, Shanshan Wan and Yee-Hong Yang. MCCG: A ConvNeXt-based Multiple-Classifier Method for Cross-view Geo-localization. TCSVT 2023 [[Code]](https://github.com/mode-str/crossview) |
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| MFJR | 91.87 | 93.15 | 95.29 | 91.51 | Ge, F., Zhang, Y., Wang, L., Liu, W., Liu, Y., Coleman, S., & Kerr, D. (2024). Multi-level Feedback Joint Representation Learning Network Based on Adaptive Area Elimination for Cross-view Geo-localization. IEEE Transactions on Geoscience and Remote Sensing. |
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|Instance Loss | 43.91 | 66.38 | 74.58 | 91.78 | Zheng Z, Zheng L, Garrett M, et al. Dual-Path Convolutional Image-Text Embedding with Instance Loss. TOMM 2020. [[Paper]](https://arxiv.org/abs/1711.05535) [[Code]](https://github.com/layumi/University1652-Baseline)|
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|RK-Net (USAM) | 52.50 | - | - | 96.52 | Lin J, Zheng Z, Zhong Z, Luo Z, Li S, Yang Y, Sebe N. Joint Representation Learning and Keypoint Detection for Cross-view Geo-localization. TIP 2022. [[Paper]](https://zdzheng.xyz/files/TIP_RKNet.pdf) [[Code]](https://github.com/AggMan96/RK-Net) |
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|CVFT | 61.43 | 84.69 | 90.49 | 99.02 | Shi Y, Yu X, Liu L, et al. Optimal Feature Transport for Cross-View Image Geo-Localization. AAAI 2020. [[Paper]](https://arxiv.org/abs/1907.05021) |
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|DWDR | 75.62 | 90.45 | 93.60 | 98.60 | Tingyu W, Zhedong Z, Zunjie Z, Yuhan G, Yi Y, and Chenggang Y. "Learning Cross-view Geo-localization Embeddings via Dynamic Weighted Decorrelation Regularization" arXiv 2022. [[Paper]](https://arxiv.org/pdf/2211.05296.pdf) |
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|DWDR | 75.62 | 90.45 | 93.60 | 98.60 | Tingyu W, Zhedong Z, Zunjie Z, Yuhan G, Yi Y, and Chenggang Y. "Learning Cross-view Geo-localization Embeddings via Dynamic Weighted Decorrelation Regularization" IEEE Transactions on Geoscience and Remote Sensing, 2024. [[Paper]](https://ieeexplore.ieee.org/document/10744586) [[Code]](https://github.com/wtyhub/DWDR) |
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|MS Attention w DataAug| 75.95 | 91.90 | 95.00 | 99.42 |Rodrigues, Royston, and Masahiro Tani. "Are These From the Same Place? Seeing the Unseen in Cross-View Image Geo-Localization." WACV 2021. [[Paper]](https://openaccess.thecvf.com/content/WACV2021/papers/Rodrigues_Are_These_From_the_Same_Place_Seeing_the_Unseen_in_WACV_2021_paper.pdf)|
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|MuSe-Net (Normal Weather) | 78.04 | - | - | - | Wang T, Zheng Z, Sun Y, et al. Multiple-environment Self-adaptive Network for Aerial-view Geo-localization[J]. Pattern Recognition, 2024. |
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|LPN| 85.79 | 95.38 | 96.98 | 99.41 | Tingyu Wang, Zhedong Zheng, Chenggang Yan, and Yi, Yang. Each Part Matters: Local Patterns Facilitate Cross-view Geo-localization. TCSVT 2021. [[Paper]](https://arxiv.org/abs/2008.11646) [[Code]](https://github.com/wtyhub/LPN)|
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|RK-Net (USAM) | 40.53 | - | - | 89.12 | Lin J, Zheng Z, Zhong Z, Luo Z, Li S, Yang Y, Sebe N. Joint Representation Learning and Keypoint Detection for Cross-view Geo-localization. TIP 2022. [[Paper]](https://zhunzhong.site/paper/RK_Net.pdf) [[Code]](https://github.com/AggMan96/RK-Net) |
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|Orientation** | 46.96 | 68.28 | 75.48 | 92.04 | Liu Liu and Hongdong Li. CVPR 2019. Lending Orientation to Neural Networks for Cross-view Geo-localization [[Paper]](https://arxiv.org/abs/1903.12351) |
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|CVFT | 61.05 | 81.33 | 86.52 | 95.93 | Shi Y, Yu X, Liu L, et al. Optimal Feature Transport for Cross-View Image Geo-Localization. AAAI 2020. [[Paper]](https://arxiv.org/abs/1907.05021) |
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|DWDR | 66.76 | 83.34 | 87.11 | 95.10 | Tingyu W, Zhedong Z, Zunjie Z, Yuhan G, Yi Y, and Chenggang Y. "Learning Cross-view Geo-localization Embeddings via Dynamic Weighted Decorrelation Regularization" arXiv 2022. [[Paper]](https://arxiv.org/pdf/2211.05296.pdf) |
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|DWDR | 66.76 | 83.34 | 87.11 | 95.10 | Tingyu W, Zhedong Z, Zunjie Z, Yuhan G, Yi Y, and Chenggang Y. "Learning Cross-view Geo-localization Embeddings via Dynamic Weighted Decorrelation Regularization" IEEE Transactions on Geoscience and Remote Sensing, 2024. [[Paper]](https://ieeexplore.ieee.org/document/10744586) [[Code]](https://github.com/wtyhub/DWDR) |
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|MS Attention w DataAug| 73.19 | 90.39 | 93.38 | 97.45 |Rodrigues, Royston, and Masahiro Tani. "Are These From the Same Place? Seeing the Unseen in Cross-View Image Geo-Localization." WACV 2021. [[Paper]](https://openaccess.thecvf.com/content/WACV2021/papers/Rodrigues_Are_These_From_the_Same_Place_Seeing_the_Unseen_in_WACV_2021_paper.pdf)|
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|LPN| 79.99 | 90.63 | 92.56 | 97.03 | Tingyu Wang, Zhedong Zheng, Chenggang Yan, and Yi, Yang. Each Part Matters: Local Patterns Facilitate Cross-view Geo-localization. TCSVT 2021. [[Paper]](https://arxiv.org/abs/2008.11646) [[Code]](https://github.com/wtyhub/LPN)|
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|LPN + CA-HRS | 80.91 | 90.95 | 92.93 | 97.07 | Zeng Lu, Tao Pu, Tianshui Chen, and Liang Lin. Content-Aware Hierarchical Representation Selection for Cross-View Geo-Localization ACCV2022. [[Paper]]([https://arxiv.org/abs/2008.11646](https://openaccess.thecvf.com/content/ACCV2022/papers/Lu_Content-Aware_Hierarchical_Representation_Selection_for_Cross-View_Geo-Localization_ACCV_2022_paper.pdf)) [[Code]](https://github.com/Allen-lz/CA-HRS) |
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|Shi etal.* | 82.70 | 92.50 | 94.24 | 97.65 | Yujiao Shi, Xin Yu, Liu Liu, Dylan Campbell, Piotr Koniusz, and Hongdong Li. Accurate 3-DoF Camera Geo-Localization via Ground-to-Satellite Image Matching. TPAMI 2022. [[Paper]](https://arxiv.org/pdf/2203.14148.pdf) [[Code]](https://github.com/shiyujiao/ibl)|
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|Toker etal.* | 83.28 | 93.57 | 95.42 | 98.22 | Aysim Toker, Qunjie Zhou, Maxim Maximov, Laura Leal-Taixé. Coming Down to Earth: Satellite-to-Street View Synthesis for Geo-Localization. CVPR 2021 [[Paper]](https://arxiv.org/pdf/2103.06818.pdf) |
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|SAFA* + LPN | 83.66 | 94.14 | 95.92 | 98.41 | Tingyu Wang, Zhedong Zheng, Chenggang Yan, and Yi, Yang. Each Part Matters: Local Patterns Facilitate Cross-view Geo-localization. TCSVT 2021. [[Paper]](https://arxiv.org/abs/2008.11646) [[Code]](https://github.com/wtyhub/LPN)|
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|LPN* + DWDR | 83.73 | 92.78 | 94.53 | 97.78 | Tingyu W, Zhedong Z, Zunjie Z, Yuhan G, Yi Y, and Chenggang Y. "Learning Cross-view Geo-localization Embeddings via Dynamic Weighted Decorrelation Regularization" arXiv 2022. [[Paper]](https://arxiv.org/pdf/2211.05296.pdf) |
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|LPN* + DWDR | 83.73 | 92.78 | 94.53 | 97.78 | Tingyu W, Zhedong Z, Zunjie Z, Yuhan G, Yi Y, and Chenggang Y. "Learning Cross-view Geo-localization Embeddings via Dynamic Weighted Decorrelation Regularization" IEEE Transactions on Geoscience and Remote Sensing, 2024. [[Paper]](https://ieeexplore.ieee.org/document/10744586) [[Code]](https://github.com/wtyhub/DWDR) |
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|Polar-L2LTR* | 84.89 | 94.59 | 95.96 | 98.37 | Hongji Yang, Xiufan Lu, Yingying Zhu. Cross-view Geo-localization with Layer-to-Layer Transformer. NeurIPS 2021 [[Paper]](https://papers.nips.cc/paper/2021/file/f31b20466ae89669f9741e047487eb37-Paper.pdf) [[Code]](https://github.com/yanghongji2007/cross_view_localization_L2LTR)|
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|TransGeo | 84.95 | 94.14 | 95.78 | 98.37 | Sijie Zhu, Mubarak Shah, Chen Chen. TransGeo: Transformer Is All You Need for Cross-view Image Geo-localization. CVPR 2022 [[Paper]](https://arxiv.org/pdf/2204.00097.pdf) [[Code]](https://github.com/jeff-zilence/transgeo2022)|
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| TransGeo + 4SCIG | 83.73 | 94.41 | 95.79 | 98.41 | Li, J., Yang, C., Qi, B., Zhu, M., & Wu, N. (2024). 4SCIG: A four-branch framework to reduce the interference of sky area in cross-view image geo-localization. IEEE Transactions on Geoscience and Remote Sensing. |

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