General-purpose vision-language models (VLMs) now support strong visual recognition, instruction following, and generation. However, most pretrained visual encoders are built around three-channel natural images and do not directly accommodate observations such as native multispectral measurements or synthetic aperture...
Shan-Ji Liu, Ke-Lu Yao, Jun-Xiao Xue et al.· 0 citations
Contrastive language-image learning (CLIP) has become a key paradigm for remote sensing vision-language understanding. However, existing remote sensing contrastive learning methods are mostly built on RGB-oriented CLIP architectures, making it difficult to exploit heterogeneous sensors such as SAR, multi-spectral imagi...
Xian-Yang Miao, Ke-Lu Yao, Ye-Hua Huang et al.· 0 citations
This work proposes SkyAnchor, an MLLM with two designs to the above challenges: a Semantics-Aware Token Router that preserves small-target under a reduced visual-token budget, and a Hierarchical Memory Bank that keeps the target consistently understood on streams.
Penglei Sun, Yehua Huang, Zhuoli Tao et al.· arXiv.org· 0 citations
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