FieryGS integrates LLM-based material reasoning, volumetric combustion simulation, and a unified renderer with 3D Gaussian Splatting to generate physically plausible and user-controllable fire in in-the-wild scenes.
Unleashing the potential of multi-modal foundation models and video diffusion for 4d dynamic physical scene simulation
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ProJo4D uses progressive joint optimization to solve sparse-view inverse physics estimation, outperforming prior methods with up to 10x better geometric accuracy in 4D state prediction and material estimation.
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FieryGS: In-the-Wild Fire Synthesis with Physics-Integrated Gaussian Splatting
FieryGS integrates LLM-based material reasoning, volumetric combustion simulation, and a unified renderer with 3D Gaussian Splatting to generate physically plausible and user-controllable fire in in-the-wild scenes.
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ProJo4D: Progressive Joint Optimization for Sparse-View Inverse Physics Estimation
ProJo4D uses progressive joint optimization to solve sparse-view inverse physics estimation, outperforming prior methods with up to 10x better geometric accuracy in 4D state prediction and material estimation.