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20242026
most citedCross-Modal Bidirectional Interaction Model for Referring Remote Sensing Image Segmentation

3 citations · 3 across the 8 of their papers we have counts for

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cs.CV2026

GeoRay: Gauge-Aware Feed-Forward Satellite 3D Reconstruction in the Geodetic Frame

Zhe Dong, Wanqing Wu, Yuzhe Sun +5

Feed-forward 3D foundation models reconstruct perspective scenes in one pass. Satellite photogrammetry needs a different product, one that domain adaptation alone does not deliver:…

cs.CV2026

ReLATE: Reliability-Guided Evidence Fusion for Robust UAV--Satellite cross-view Geo-Localization

Haochen Jiang, Jialei Pan, Yuzhe Sun +4

Unmanned aerial vehicle (UAV)-satellite cross-view geo-localization matches UAV images against satellite imagery and has achieved impressive accuracy on clean (non-degraded) image…

cs.CV2026

CroBIM-V: Memory-Quality Controlled Remote Sensing Referring Video Object Segmentation

H. Jiang, Y. Sun, Z. Dong +2

Remote sensing video referring object segmentation (RS-RVOS) is challenged by weak target saliency and severe visual information truncation in dynamic scenes, making it extremely d…

cs.CV2026

CroBIM-U: Uncertainty-Driven Referring Remote Sensing Image Segmentation

Yuzhe Sun, Zhe Dong, Haochen Jiang +2

Referring remote sensing image segmentation aims to localize specific targets described by natural language within complex overhead imagery. However, due to extreme scale variation…

cs.CV2025

PhyDAE: Physics-Guided Degradation-Adaptive Experts for All-in-One Remote Sensing Image Restoration

Zhe Dong, Yuzhe Sun, Haochen Jiang +2

Remote sensing images inevitably suffer from various degradation factors during acquisition, including atmospheric interference, sensor limitations, and imaging conditions. These c…

cs.CV2025

DiffRIS: Enhancing Referring Remote Sensing Image Segmentation with Pre-trained Text-to-Image Diffusion Models

Zhe Dong, Yuzhe Sun, Tianzhu Liu +1

Referring remote sensing image segmentation (RRSIS) enables the precise delineation of regions within remote sensing imagery through natural language descriptions, serving critical…