7 papers
SARATR-X-v2: Scale-Aware Structural Pre-Training for SAR Foundation Models
Weijie Li, Yafei Song, Yongxiang Liu +7
Masked image modeling has become a dominant paradigm for SAR pre-training, yet the design of the reconstruction target remains fundamentally unsettled. This article argues that a S…
Better with Less: Tackling Heterogeneous Multi-Modal Image Joint Pretraining via Conditioned and Degraded Masked Autoencoder
Bowen Peng, Yongxiang Liu, Jie Zhou +4
Learning robust representations across extremely heterogeneous modalities remains a fundamental challenge in multi-modal vision. As a critical and profound instantiation of this ch…
HuiYanEarth-SAR: A Foundation Model for High-Fidelity and Low-Cost Global Remote Sensing Imagery Generation
Yongxiang Liu, Jie Zhou, Yafei Song +2
Synthetic Aperture Radar (SAR) imagery generation is essential for deepening the study of scattering mechanisms, establishing trustworthy electromagnetic scene models, and fundamen…
ATRNet-STAR: A Large Dataset and Benchmark Towards Remote Sensing Object Recognition in the Wild
Yongxiang Liu, Weijie Li, Li Liu +8
The absence of publicly available, large-scale, high-quality datasets for Synthetic Aperture Radar Automatic Target Recognition (SAR ATR) has significantly hindered the application…
Step-wise Distribution Alignment Guided Style Prompt Tuning for Source-free Cross-domain Few-shot Learning
Huali Xu, Li Liu, Tianpeng Liu +3
Existing cross-domain few-shot learning (CDFSL) methods, which develop source-domain training strategies to enhance model transferability, face challenges with large-scale pre-trai…
MaDiNet: Mamba Diffusion Network for SAR Target Detection
Jie Zhou, Chao Xiao, Bowen Peng +4
The fundamental challenge in SAR target detection lies in developing discriminative, efficient, and robust representations of target characteristics within intricate non-cooperativ…