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cs.CV2026
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…
cs.CV2026
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…
cs.CV2026
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…