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LEVIRDet-159 not only sets a new standard in dataset scale but also enables a foundation model that generalizes effectively across diverse remote sensing contexts.
Achieving linear-time efficiency in remote sensing instance segmentation could revolutionize how we deploy vision models in resource-constrained environments.
SSMs are revolutionizing remote sensing by efficiently tackling complex data challenges, yet many researchers remain unaware of their full potential.
Scale-Frustum Representations offer a surprisingly effective way to model objects at drastically different scales in ultra-wide area remote sensing images, boosting segmentation accuracy and convergence speed.
