MrNeRF (@janusch_patas)
2025-10-15 | โค๏ธ 80 | ๐ 8
Uncertainty Matters in Dynamic Gaussian Splatting for Monocular 4D Reconstruction
Abstract (excerpt): While dynamic Gaussian Splatting offers an efficient representation, vanilla models optimize all Gaussian primitives uniformly, ignoring whether they are well or poorly observed. This limitation leads to motion drifts under occlusion and degraded synthesis when extrapolating to unseen views.
We argue that uncertainty matters: Gaussians with recurring observations across views and time act as reliable anchors to guide motion, whereas those with limited visibility are treated as less reliable.
To this end, we introduce USplat4D, a novel Uncertainty-aware dynamic Gaussian Splatting framework that propagates reliable motion cues to enhance 4D reconstruction. Our key insight is to estimate time-varying per-Gaussian uncertainty and leverage it to construct a spatio-temporal graph for uncertainty-aware optimization.
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