Exploring the Potential of Contrastive Language-Image Pre-training for Multi-Source Remote Sensing Data
OmniRSCLIP is an end-to-end contrastive learning framework that supports multi-source sensor inputs for remote sensing vision-language modeling and introduces a spectral-context-aware mask-based contrastive learning scheme to suppress modality-specific redundant features and enhance fine-grained image-text alignment.
Xian-Yang Miao, Ke-Lu Yao, Ye-Hua Huang et al.
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