Let it Snow! Animating Static Gaussian Scenes With Dynamic Weather Effects

2025-04-07

AI Summary

Static 3D Gaussian splatting struggles to naturally integrate dynamic weather effects—such as snow, rain, fog, and dust—and model their physical interactions with static scenes. Method: We propose a Gaussian-particle hybrid representation framework. Leveraging a novel bidirectional mapping mechanism, it jointly models physically grounded dynamic elements (simulated via the Material Point Method) and static Gaussian scenes at both geometric and appearance levels. We design a Gaussian-domain appearance parameterization mapping and a customized collision response algorithm to enable precise particle–Gaussian voxel interactions. The method tightly couples 3D Gaussian rasterization with particle systems. Contribution/Results: Our approach preserves real-time rendering efficiency while significantly improving the physical plausibility and visual fidelity of dynamic weather. It supports high-frame-rate, high-fidelity synthesis of diverse complex weather effects, establishing a new paradigm for neural rendering and dynamic scene modeling.

Technology Category

• Computer Vision: 3D Computer Vision
• Knowledge Representation and Reasoning: Geometric, Spatial, and Temporal Reasoning
• Humans and AI: Human-Aware Planning and Behavior Prediction

Application Category

• Graph Algorithms and Modeling for the Web: Efficient manipulation of static and dynamic Web-related graphs
• Systems and Infrastructure for Web, Mobile and WoT: Web applications in cross-disciplinary domains and verticals such as mixed reality, smart cities, and digital health
• User Modeling, Personalization and Recommendation: User modeling and simulation for interactive and conversational systems

Abstract

3D Gaussian Splatting has recently enabled fast and photorealistic reconstruction of static 3D scenes. However, introducing dynamic elements that interact naturally with such static scenes remains challenging. Accordingly, we present a novel hybrid framework that combines Gaussian-particle representations for incorporating physically-based global weather effects into static 3D Gaussian Splatting scenes, correctly handling the interactions of dynamic elements with the static scene. We follow a three-stage process: we first map static 3D Gaussians to a particle-based representation. We then introduce dynamic particles and simulate their motion using the Material Point Method (MPM). Finally, we map the simulated particles back to the Gaussian domain while introducing appearance parameters tailored for specific effects. To correctly handle the interactions of dynamic elements with the static scene, we introduce specialized collision handling techniques. Our approach supports a variety of weather effects, including snowfall, rainfall, fog, and sandstorms, and can also support falling objects, all with physically plausible motion and appearance. Experiments demonstrate that our method significantly outperforms existing approaches in both visual quality and physical realism.

Problem

• Introducing dynamic weather effects into static 3D Gaussian scenes
• Handling interactions between dynamic elements and static scenes
• Achieving physically plausible motion and appearance for effects

Innovation

• Hybrid Gaussian-particle framework for dynamic weather
• Material Point Method for particle motion simulation
• Specialized collision handling for static-dynamic interaction