MVFusion-GS: Motion Variance Guides Dynamic Gaussian Splatting
zhenjun_zhao · x · 2026-07-03
The paper MVFusion-GS proposes a new method for high-quality Dynamic Gaussian Splatting, with its core innovation being a motion variance-guided temporal attention mechanism.
The method works in two steps: ① Automatically separating dynamic and static regions by calculating motion variance based on the deformation statistics of each Gaussian; ② Modeling temporal motion dependencies through cross-frame cross-attention to enhance the coherence and realism of dynamic scene rendering.
This research offers a novel solution for temporal consistency in dynamic 3D scene reconstruction and rendering. The paper is now available on arXiv.
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