MobileGeo: Exploring Hierarchical Knowledge Distillation for Resource-Efficient Cross-view Drone Geo-Localization

TL;DR

MobileGeo introduces a resource-efficient framework for drone cross-view geo-localization, utilizing hierarchical knowledge distillation and view filtering to achieve high accuracy and real-time performance on edge devices.

Contribution

The paper presents MobileGeo, a novel mobile-friendly CVGL framework with hierarchical distillation and view filtering, reducing inference costs while maintaining state-of-the-art accuracy.

Findings

Achieves 4.19% higher AP on University1652 dataset.

Over 5 times reduction in FLOPs compared to previous methods.

Runs at 251.5 FPS on NVIDIA AGX Orin edge device.

Abstract

Cross-view geo-localization (CVGL) plays a vital role in drone-based multimedia applications, enabling precise localization by matching drone-captured aerial images against geo-tagged satellite databases in GNSS-denied environments. However, existing methods rely on resource-intensive feature alignment and multi-branch architectures, incurring high inference costs that limit their deployment on edge devices. We propose MobileGeo, a mobile-friendly framework designed for efficient on-device CVGL: 1) During training, a Hierarchical Distillation (HD-CVGL) paradigm, coupled with Uncertainty-Aware Prediction Alignment (UAPA), distills essential information into a compact model without incurring inference overhead. 2) During inference, an efficient Multi-view Selection Refinement Module (MSRM) leverages mutual information to filter redundant views and reduce computational load. Extensive experiments demonstrate that MobileGeo outperforms previous state-of-the-art methods, achieving a 4.19% improvement in AP on University1652 dataset while being over 5 times efficient in FLOPs and 3 times faster. Crucially, MobileGeo runs at 251.5 FPS on an NVIDIA AGX Orin edge device, demonstrating its practical viability for real-time on-device drone geo-localization. The code is available at https://github.com/SkyEyeLoc/MobileGeo.