3 papers
cs.CV2025
RingMoE: Mixture-of-Modality-Experts Multi-Modal Foundation Models for Universal Remote Sensing Image Interpretation
Hanbo Bi, Yingchao Feng, Boyuan Tong +11
The rapid advancement of foundation models has revolutionized visual representation learning in a self-supervised manner. However, their application in remote sensing (RS) remains…
cs.CV2025
RingMo-Aerial: An Aerial Remote Sensing Foundation Model With Affine Transformation Contrastive Learning
Wenhui Diao, Haichen Yu, Kaiyue Kang +8
Aerial Remote Sensing (ARS) vision tasks present significant challenges due to the unique viewing angle characteristics. Existing research has primarily focused on algorithms for s…
cs.CV2025
ViRefSAM: Visual Reference-Guided Segment Anything Model for Remote Sensing Segmentation
Hanbo Bi, Yulong Xu, Ya Li +8
The Segment Anything Model (SAM), with its prompt-driven paradigm, exhibits strong generalization in generic segmentation tasks. However, applying SAM to remote sensing (RS) images…