AI RESEARCH
Observe Less, Understand More: Cost-aware Cross-scale Observation for Remote Sensing Understanding
arXiv CS.CV
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ArXi:2604.11415v1 Announce Type: new Remote sensing understanding inherently requires multi-resolution observation, since different targets and application tasks demand different levels of spatial detail. While low-resolution (LR) imagery enables efficient global observation, high-resolution (HR) imagery provides critical local details at much higher acquisition cost and limited coverage. This motivates a cross-scale sensing strategy that selectively acquires HR imagery from LR-based global perception to improve task performance under constrained cost.