Rouwan Wu — accepted AI-conference papers

2026

AerialExtreMatch: A Benchmark for Extreme-View Image Matching and Localization

Rouwan Wu, Zhe Huang, Xingyi He, Yan Liu, Shen Yan, Sida Peng +2

RA-L 2026

Image matching serves as a core component for UAV localization guided by satellite imagery. However, this task remains highly challenging due to the extreme viewpoint discrepancies between low-altitude UAV images and nadir-view satellite maps. Existing datasets primarily focus on ground-level or hig

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2026

NGC-GeoLoc: Neural GeoCoordinate Regression for GPS-Denied UAV Geo-Localization

Jiacheng Deng, Rouwan Wu, Maojun Zhang, Shen Yan

RA-L 2026

Visual geo-localization without GPS prior remains a significant challenge for UAV navigation. Traditional retrievalbased methods suffer from scale and rotation variances between UAV images and satellite maps, and their inference speed degrades with increasing map size. To address these challenges, w

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