AI RESEARCH
Flow-based Gaussian Splatting for Continuous-Scale Remote Sensing Image Super-Resolution
arXiv CS.CV
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ArXi:2605.22147v1 Announce Type: new High-resolution remote sensing images (RSIs) are crucial for Earth observation applications, yet acquiring them is often limited by sensor constraints and costs. In recent years, generative super-resolution (SR) methods, particularly diffusion models, have made significant progress. However, they typically require slow iterative inference with 40--1000 steps and exhibit limited flexibility in continuous-scale SR settings. To address these issues, we propose FlowGS, a generative reconstruction framework for arbitrary-scale SR of RSIs.