# Orientation-Guided Contrastive Learning for UAV-View Geo-Localisation

arXiv: https://arxiv.org/abs/2308.00982 · HTML: https://mlsanity.com/paper/2308.00982/

## Key facts

- Cited by 7 papers in the map (data through 14 Oct 2026).
- Builds on 27 of its 42 references that are in the map.
- First posted on arXiv 2 Aug 2023.

## Builds on (most cited first, 27 of 27)

- [BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding](https://mlsanity.com/paper/1810.04805/) (2018)
- [Learning Transferable Visual Models From Natural Language Supervision](https://mlsanity.com/paper/2103.00020/) (2021)
- [DINOv2: Learning Robust Visual Features without Supervision](https://mlsanity.com/paper/2304.07193/) (2023)
- [Representation Learning with Contrastive Predictive Coding](https://mlsanity.com/paper/1807.03748/) (2018)
- [Momentum Contrast for Unsupervised Visual Representation Learning](https://mlsanity.com/paper/1911.05722/) (2019)
- [LAION-5B: An open large-scale dataset for training next generation image-text models](https://mlsanity.com/paper/2210.08402/) (2022)
- [A ConvNet for the 2020s](https://mlsanity.com/paper/2201.03545/) (2022)
- [SuperPoint: Self-Supervised Interest Point Detection and Description](https://mlsanity.com/paper/1712.07629/) (2017)
- [Block-NeRF: Scalable Large Scene Neural View Synthesis](https://mlsanity.com/paper/2202.05263/) (2022)
- [From Coarse to Fine: Robust Hierarchical Localization at Large Scale](https://mlsanity.com/paper/1812.03506/) (2018)
- [Mega-NeRF: Scalable Construction of Large-Scale NeRFs for Virtual Fly-Throughs](https://mlsanity.com/paper/2112.10703/) (2021)
- [VIGOR: Cross-View Image Geo-localization beyond One-to-one Retrieval](https://mlsanity.com/paper/2011.12172/) (2020)
- [Wide-Area Image Geolocalization with Aerial Reference Imagery](https://mlsanity.com/paper/1510.03743/) (2015)
- [Lending Orientation to Neural Networks for Cross-view Geo-localization](https://mlsanity.com/paper/1903.12351/) (2019)
- [TransGeo: Transformer Is All You Need for Cross-view Image Geo-localization](https://mlsanity.com/paper/2204.00097/) (2022)
- [University-1652: A Multi-view Multi-source Benchmark for Drone-based Geo-localization](https://mlsanity.com/paper/2002.12186/) (2020)
- [Where am I looking at? Joint Location and Orientation Estimation by Cross-View Matching](https://mlsanity.com/paper/2005.03860/) (2020)
- [Sample4Geo: Hard Negative Sampling For Cross-View Geo-Localisation](https://mlsanity.com/paper/2303.11851/) (2023)
- [Each Part Matters: Local Patterns Facilitate Cross-view Geo-localization](https://mlsanity.com/paper/2008.11646/) (2020)
- [Beyond Cross-view Image Retrieval: Highly Accurate Vehicle Localization Using Satellite Image](https://mlsanity.com/paper/2204.04752/) (2022)
- [Cross-view Geo-localization via Learning Disentangled Geometric Layout Correspondence](https://mlsanity.com/paper/2212.04074/) (2022)
- [A Transformer-Based Feature Segmentation and Region Alignment Method For UAV-View Geo-Localization](https://mlsanity.com/paper/2201.09206/) (2022)
- [Revisiting Street-to-Aerial View Image Geo-localization and Orientation Estimation](https://mlsanity.com/paper/2005.11592/) (2020)
- [Optimization of Indexing Based on k-Nearest Neighbor Graph for Proximity Search in High-dimensional Data](https://mlsanity.com/paper/1810.07355/) (2018)
- [Learning Cross-view Geo-localization Embeddings via Dynamic Weighted Decorrelation Regularization](https://mlsanity.com/paper/2211.05296/) (2022)
- [Accurate Visual Localization for Automotive Applications](https://mlsanity.com/paper/1905.03706/) (2019)
- [Multi-view Drone-based Geo-localization via Style and Spatial Alignment](https://mlsanity.com/paper/2006.13681/) (2020)

## Built on by (most cited first, 7 of 7)

- [EarthLoc: Astronaut Photography Localization by Indexing Earth from Space](https://mlsanity.com/paper/2403.06758/) (2024)
- [Cross-View Image Set Geo-Localization](https://mlsanity.com/paper/2412.18852/) (2024)
- [Object-aware graph matching network for cross-domain remote sensing image localization](https://mlsanity.com/paper/2511.02489/) (2025)
- [GeoVLM: Improving Automated Vehicle Geolocalisation Using Vision-Language Matching](https://mlsanity.com/paper/2505.13669/) (2025)
- [AstroLoc: Robust Space to Ground Image Localizer](https://mlsanity.com/paper/2502.07003/) (2025)
- [Locality-Sensitive Hashing for Efficient Hard Negative Sampling in Contrastive Learning](https://mlsanity.com/paper/2505.17844/) (2025)
- [Road Maps as Free Geometric Priors: Weather-Invariant Drone Geo-Localization with GeoFuse](https://mlsanity.com/paper/2605.14925/) (2026)

## Abstract (arXiv)

Retrieving relevant multimedia content is one of the main problems in a world that is increasingly data-driven. With the proliferation of drones, high quality aerial footage is now available to a wide audience for the first time. Integrating this footage into applications can enable GPS-less geo-localisation or location correction. In this paper, we present an orientation-guided training framework for UAV-view geo-localisation. Through hierarchical localisation orientations of the UAV images are estimated in relation to the satellite imagery. We propose a lightweight prediction module for these pseudo labels which predicts the orientation between the different views based on the contrastive learned embeddings. We experimentally demonstrate that this prediction supports the training and outperforms previous approaches. The extracted pseudo-labels also enable aligned rotation of the satellite image as augmentation to further strengthen the generalisation. During inference, we no longer need this orientation module, which means that no additional computations are required. We achieve state-of-the-art results on both the University-1652 and University-160k datasets.