FogGS: Physics-Grounded 3D Foggy Effects

Realistic and diverse fog synthesis is a critical capability in 3D scene modelling, with broad applications in autonomous driving simulation, cinematic visual effects, gaming, and AR/VR. Yet achieving this, encompassing varied density profiles, spatial distributions, and complex optical phenomena, in real-world scenes remains a largely unsolved challenge. Existing approaches rely on appearance-driven weather transfer or simple fog overlays, which lack the physical grounding needed for volumetric effects and thus cannot faithfully model key fog properties and effects, including density gradients, anisotropic scattering, and atmospheric light shafts (Tyndall effect) — \textit{limitations} that stem directly from the absence of explicit volumetric representation and physical light transport modeling. We present \textbf{FogGS}, a training-free, model-agnostic rendering framework that seamlessly enables existing pretrained fog-free 3DGS models to produce photorealistic, physically plausible, and fully editable fog in novel-view synthesis. Grounded in atmospheric radiative transfer theory, FogGS models fog as spatially varying extinction and scattering fields, using the depth buffer from Gaussian rasterization to drive efficient screen-space ray marching for geometry-aligned transmittance and in-scattering computation. This physically grounded parameterization affords intuitive control over fog intensity, appearance, and spatial distribution, and naturally supports anisotropic scattering, scene occlusion, and illumination. FogGS maintains high rendering efficiency practical for iterative editing workflows, remains compatible with relighting pipelines, and demonstrates superior realism, physical consistency, and controllability across diverse outdoor scenes.