TL;DR
An adaptive framework for cross-view matching that integrates spectrum adaptive enhancement and multi-scale semantic interaction mechanisms is proposed that leverages frequency-domain information to strengthen structural and detailed features, and employs multi-scale semantic guidance to improve feature alignment.
Visual geo-localization seeks to enable autonomous aircraft positioning in GNSS-denied environments through large-scale image retrieval. Most existing methods, however, primarily rely on visible light images and are thus inherently sensitive to illumination changes and adverse weather conditions. Near-infrared (NIR) im...
Cross-view geo-localization (CVGL) aims at localizing a ground-level query by retrieving its corresponding match from a database of geo-tagged satellite images. Existing multi-modal CVGL methods lack a structured design in the fusion stage, limiting their ability to fully exploit the information from multiple modalitie...
Cross-view geo-localization (CVGL) aims to match images captured from different viewpoints, such as drone and satellite imagery. Existing methods primarily focus on single-image matching, overlooking the potential of leveraging temporal information from drone image sequences. To address this, we propose Spatio-Temporal...
Multiview geo-localization utilizing drone and satellite imagery offers a reliable alternative to GPS-based positioning in challenging environments such as urban canyons and electromagnetically degraded areas. A key challenge in this task stems from the spatial misalignment between drone-view and satellite-view images,...
This work proposes a novel CVGL method named dynamic-feature collaborative optimization and semantic-alignment network (DFSA), designed to extract robust feature representations and achieve fine-grained alignment, and introduces a semantic segmentation and alignment module that adaptively partitions images into semanti...
A scale-aware fusion and apatial-frequency collaborative network (SFSNet) is proposed to enhance multiscale feature representation through cross-level feature interaction, multireceptive-field calibration, and cross-stage channel fusion, thereby alleviating the suppression of small-scale objects by background regions a...
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