10 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…
RoadGIE: Towards A Global-Scale Aerial Benchmark for Generalizable Interactive Road Extraction
Chenxu Peng, Chenxu Wang, Yimian Dai +3
Accurate road segmentation from aerial imagery is fundamental to many geospatial applications. However, existing datasets often suffer from limited scene diversity, low semantic gr…
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…
Fifty Years of SAR Automatic Target Recognition: The Road Forward
Jie Zhou, Yongxiang Liu, Li Liu +6
Synthetic Aperture Radar (SAR) imaging is capable of observing objects in nearly all weather and illumination conditions, and has become an indispensable means of information acqui…
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…