Weather-Magician: Reconstruction and Rendering Framework for 4D Weather Synthesis In Real Time
Chen Sang, Yeqiang Qian, Jiale Zhang, Chunxiang Wang, Ming Yang

TL;DR
Weather-Magician is a real-time framework that reconstructs and renders 4D weather effects in scenes using Gaussian splatting, enabling efficient, high-quality, dynamic weather simulation for applications like digital twins and VR.
Contribution
It introduces a novel Gaussian splatting-based framework for real-time 4D weather reconstruction and rendering, supporting dynamic weather changes with low hardware requirements.
Findings
Supports real-time weather simulation with high visual fidelity.
Enables continuous dynamic weather changes in reconstructed scenes.
Operates efficiently on low hardware requirements.
Abstract
For tasks such as urban digital twins, VR/AR/game scene design, or creating synthetic films, the traditional industrial approach often involves manually modeling scenes and using various rendering engines to complete the rendering process. This approach typically requires high labor costs and hardware demands, and can result in poor quality when replicating complex real-world scenes. A more efficient approach is to use data from captured real-world scenes, then apply reconstruction and rendering algorithms to quickly recreate the authentic scene. However, current algorithms are unable to effectively reconstruct and render real-world weather effects. To address this, we propose a framework based on gaussian splatting, that can reconstruct real scenes and render them under synthesized 4D weather effects. Our work can simulate various common weather effects by applying Gaussians modeling…
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Taxonomy
TopicsComputer Graphics and Visualization Techniques · Simulation and Modeling Applications · Advanced Vision and Imaging
