74 citations · 92 across the 7 of their papers we have counts for
5 papers · 1 filter
T-JEPA: A Temporal Joint-Embedding Predictive Architecture for Learning Better Remote Sensing Representations
Bowen Peng, Li Liu, Yongxiang Liu +3
Earth observation (EO) data provide rich temporal supervision, yet existing remote sensing foundation models mainly exploit sequential observations through imposing predefined pair…
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…
MMATR-X: High-Resolution Optical-SAR Joint Pretraining via Conditioned Alignment and Degraded-Target Prediction
Bowen Peng, Yongxiang Liu, Jie Zhou +4
Joint optical and Synthetic Aperture Radar (SAR) pretraining seeks cross-modal gains over representations learned from either modality alone. This is challenging because the modali…
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…