# Multi-weather Cross-view Geo-localization Using Denoising Diffusion Models

arXiv: https://arxiv.org/abs/2408.02408 · HTML: https://mlsanity.com/paper/2408.02408/

## Key facts

- Cited by 11 papers in the map (data through 14 Oct 2026).
- Builds on 16 of its 23 references that are in the map.
- First posted on arXiv 5 Aug 2024.

## Builds on (most cited first, 16 of 16)

- [An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale](https://mlsanity.com/paper/2010.11929/) (2020)
- [Swin Transformer: Hierarchical Vision Transformer using Shifted Windows](https://mlsanity.com/paper/2103.14030/) (2021)
- [EVA-02: A Visual Representation for Neon Genesis](https://mlsanity.com/paper/2303.11331/) (2023)
- [TransWeather: Transformer-based Restoration of Images Degraded by Adverse Weather Conditions](https://mlsanity.com/paper/2111.14813/) (2021)
- [Restoring Vision in Adverse Weather Conditions with Patch-Based Denoising Diffusion Models](https://mlsanity.com/paper/2207.14626/) (2022)
- [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)
- [An Extensible Framework for Open Heterogeneous Collaborative Perception](https://mlsanity.com/paper/2401.13964/) (2024)
- [Deep Dense Multi-scale Network for Snow Removal Using Semantic and Geometric Priors](https://mlsanity.com/paper/2103.11298/) (2021)
- [Asynchrony-Robust Collaborative Perception via Bird's Eye View Flow](https://mlsanity.com/paper/2309.16940/) (2023)
- [Boosting 3-DoF Ground-to-Satellite Camera Localization Accuracy via Geometry-Guided Cross-View Transformer](https://mlsanity.com/paper/2307.08015/) (2023)
- [Accurate 3-DoF Camera Geo-Localization via Ground-to-Satellite Image Matching](https://mlsanity.com/paper/2203.14148/) (2022)
- [Multiple-environment Self-adaptive Network for Aerial-view Geo-localization](https://mlsanity.com/paper/2204.08381/) (2022)
- [CVLNet: Cross-View Semantic Correspondence Learning for Video-based Camera Localization](https://mlsanity.com/paper/2208.03660/) (2022)
- [Learning Dense Flow Field for Highly-accurate Cross-view Camera Localization](https://mlsanity.com/paper/2309.15556/) (2023)
- [BM2CP: Efficient Collaborative Perception with LiDAR-Camera Modalities](https://mlsanity.com/paper/2310.14702/) (2023)

## Built on by (most cited first, 11 of 11)

- [Embodied AI: From LLMs to World Models](https://mlsanity.com/paper/2509.20021/) (2025)
- [WeatherPrompt: Multi-modality Representation Learning for All-Weather Drone Visual Geo-Localization](https://mlsanity.com/paper/2508.09560/) (2025)
- [Scale-adaptive UAV Geo-localization via Height-aware Partition Learning](https://mlsanity.com/paper/2412.11535/) (2024)
- [DiffusionUavLoc: Visually Prompted Diffusion for Cross-View UAV Localization](https://mlsanity.com/paper/2511.06422/) (2025)
- [Self-evolving Embodied AI](https://mlsanity.com/paper/2602.04411/) (2026)
- [RHO: Robust Holistic OSM-Based Metric Cross-View Geo-Localization](https://mlsanity.com/paper/2603.27758/) (2026)
- [Weather-Robust Cross-View Geo-Localization via Prototype-Based Semantic Part Discovery](https://mlsanity.com/paper/2605.11654/) (2026)
- [Salient Object Detection in Complex Weather Conditions via Noise Indicators](https://mlsanity.com/paper/2512.10592/) (2025)
- [GeoLink: A 3D-aware Framework to Improve Generalization for Cross-view Geo-localization](https://mlsanity.com/paper/2604.13183/) (2026)
- [ReLATE: Reliability-Guided Evidence Fusion for Robust UAV--Satellite cross-view Geo-Localization](https://mlsanity.com/paper/2607.25524/) (2026)
- [AerialDojo-200K: A Large-Scale Benchmark Suite for Open-World Aerial Object-Goal Search](https://mlsanity.com/paper/2609.36066/) (2026)

## Abstract (arXiv)

Cross-view geo-localization in GNSS-denied environments aims to determine an unknown location by matching drone-view images with the correct geo-tagged satellite-view images from a large gallery. Recent research shows that learning discriminative image representations under specific weather conditions can significantly enhance performance. However, the frequent occurrence of unseen extreme weather conditions hinders progress. This paper introduces MCGF, a Multi-weather Cross-view Geo-localization Framework designed to dynamically adapt to unseen weather conditions. MCGF establishes a joint optimization between image restoration and geo-localization using denoising diffusion models. For image restoration, MCGF incorporates a shared encoder and a lightweight restoration module to help the backbone eliminate weather-specific information. For geo-localization, MCGF uses EVA-02 as a backbone for feature extraction, with cross-entropy loss for training and cosine distance for testing. Extensive experiments on University160k-WX demonstrate that MCGF achieves competitive results for geo-localization in varying weather conditions.