X-GS: An Extensible Framework for Perceiving and Thinking with 3D Gaussian Splatting
3D Gaussian Splatting (3DGS) has emerged as a powerful technique for novel view synthesis, subsequently extending into numerous spatial AI applications. However, most existing 3DGS methods operate in isolation, focusing on specific domains. In this paper, we introduce X-GS, an extensible framework that integrates previously isolated 3DGS methods into the perception module of a VLM for spatial tasks, with two major components: the $\textit{Perceiver}$ and the $\textit{Thinker}$. The $\textit{Perceiver}$ performs online 3DGS-based SLAM with semantic distillation and outputs semantic Gaussians from unposed video streams. It leverages recent vision foundation models for stronger geometric pri...
| Authors | Yueen Ma, Zenglin Xu, Irwin King |
|---|---|
| Primary category | cs.CV |
| Published | 10 March 2026 |
| Last updated at source | 20 September 2026 |
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