MeteGS：Meteorology-Guided Gaussian Splatting for Scene Rendering and Recovery in Adverse Weather Conditions

摘要

3D Gaussian Splatting enables efficient, high-fidelity novel view synthesis with explicit Gaussians and differentiable rendering. However, adverse weather introduces rain streaks and droplets as well as volumetric scattering, producing view-dependent, spatially varying degradations that break the clean multi-view consistency assumption and lead to geometric drift and unstable appearance. Existing approaches are largely confined to the 2D image domain and seldom model the 3D degradation formation process, limiting controllable weather synthesis and consistent restoration in 3DGS. To our knowledge, we are the first to incorporate real meteorological observations as an external prior and propose a 3D-level unified rendering–restoration framework for joint deraining and dehazing within a single 3DGS pipeline. Precipitation is mapped to interpretable parameters controlling the density and morphology of rain Gaussians, while an atmospheric-scattering extinction strength drives 3D fog generation for reproducible weather modeling. We adopt a closed-loop dual-branch optimization where the rendering branch fits degraded observations to capture weather degradation patterns, and the restoration branch regularizes scene Gaussians toward a clean domain with multi-scale perceptual consistency, suppressing artifacts and improving cross-view detail fidelity. Experiments across diverse scenes and weather conditions consistently outperform strong baselines on all three metrics, with a particularly notable PSNR improvement of 1.78 dB on average.