X-GS: An Extensible Open Framework for Perceiving and Thinking via 3D Gaussian Splatting

• URL: http://arxiv.org/abs/2603.09632v2
• Date: Thu, 12 Mar 2026 07:14:05 GMT
• Title: X-GS: An Extensible Open Framework for Perceiving and Thinking via 3D Gaussian Splatting
• Abstract summary: We introduce X-GS, an open framework consisting of two major components: the X-GS-Perceiver and the X-GS-Thinker.<n>The Perceiver unifies a broad range of 3DGS techniques to enable real-time online SLAM and distill semantic features.<n>The Thinker accommodates vision-sampling models and utilizes the resulting 3D semantic Gaussians, enabling downstream applications such as object detection, caption generation, and potentially embodied tasks.
• Score: 72.02343855552051
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: 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 such as pose-free 3DGS, online SLAM, and semantic enrichment. In this paper, we introduce X-GS, an extensible open framework consisting of two major components: the X-GS-Perceiver, which unifies a broad range of 3DGS techniques to enable real-time online SLAM and distill semantic features; and the X-GS-Thinker, which interfaces with downstream multimodal models. In our implementation of the Perceiver, we integrate various 3DGS methods through three novel mechanisms: an online Vector Quantization (VQ) module, a GPU-accelerated grid-sampling scheme, and a highly parallelized pipeline design. The Thinker accommodates vision-language models and utilizes the resulting 3D semantic Gaussians, enabling downstream applications such as object detection, caption generation, and potentially embodied tasks. Experimental results on real-world datasets demonstrate the efficiency and newly unlocked multimodal capabilities of the X-GS framework.

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