GaussianSSC: Triplane-Guided Directional Gaussian Fields for 3D Semantic Completion
We present \emph{GaussianSSC}, a two-stage, grid-native and triplane-guided approach to semantic scene completion (SSC) that injects the benefits of Gaussians without replacing the voxel grid or maintaining a separate Gaussian set. We introduce \emph{Gaussian Anchoring}, a sub-pixel, Gaussian-weighted image aggregation over fused FPN features that tightens voxel--image alignment and improves monocular occupancy estimation. We further convert point-like voxel features into a learned per-voxel Gaussian field and refine triplane features via a triplane-aligned \emph{Gaussian--Triplane Refinement} module that combines \emph{local gathering} (target-centric) and \emph{global aggregation} (sour...
| Authors | Ruiqi Xian, Jing Liang, He Yin et al. |
|---|---|
| Primary category | cs.RO |
| Published | 23 March 2026 |
| Last updated at source | 23 March 2026 |
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