70 citations · 223 across the 19 of their papers we have counts for
19 papers · 1 filter
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…
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…
AgMTR: Agent Mining Transformer for Few-shot Segmentation in Remote Sensing
Hanbo Bi, Yingchao Feng, Yongqiang Mao +4
Few-shot Segmentation (FSS) aims to segment the interested objects in the query image with just a handful of labeled samples (i.e., support images). Previous schemes would leverage…
Prompt-and-Transfer: Dynamic Class-aware Enhancement for Few-shot Segmentation
Hanbo Bi, Yingchao Feng, Wenhui Diao +5
For more efficient generalization to unseen domains (classes), most Few-shot Segmentation (FSS) would directly exploit pre-trained encoders and only fine-tune the decoder, especial…
SCLNet: A Scale-Robust Complementary Learning Network for Object Detection in UAV Images
Xuexue Li
Most recent UAV (Unmanned Aerial Vehicle) detectors focus primarily on general challenge such as uneven distribution and occlusion. However, the neglect of scale challenges, which…
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…