SIMSplat: Predictive Driving Scene Editing with Language-aligned 4D Gaussian Splatting

• URL: http://arxiv.org/abs/2510.02469v1
• Date: Thu, 02 Oct 2025 18:22:03 GMT
• Title: SIMSplat: Predictive Driving Scene Editing with Language-aligned 4D Gaussian Splatting
• Authors: Sung-Yeon Park, Adam Lee, Juanwu Lu, Can Cui, Luyang Jiang, Rohit Gupta, Kyungtae Han, Ahmadreza Moradipari, Ziran Wang,
• Abstract summary: SIMSplat is a predictive driving scene editor with language-aligned Gaussian splatting.<n>As a language-controlled editor, SIMSplat enables intuitive manipulation using natural language prompts.<n>Our method provides detailed object-level editing, including adding new objects and modifying the trajectories of both vehicles and pedestrians.
• Score: 11.176642816523824
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: Driving scene manipulation with sensor data is emerging as a promising alternative to traditional virtual driving simulators. However, existing frameworks struggle to generate realistic scenarios efficiently due to limited editing capabilities. To address these challenges, we present SIMSplat, a predictive driving scene editor with language-aligned Gaussian splatting. As a language-controlled editor, SIMSplat enables intuitive manipulation using natural language prompts. By aligning language with Gaussian-reconstructed scenes, it further supports direct querying of road objects, allowing precise and flexible editing. Our method provides detailed object-level editing, including adding new objects and modifying the trajectories of both vehicles and pedestrians, while also incorporating predictive path refinement through multi-agent motion prediction to generate realistic interactions among all agents in the scene. Experiments on the Waymo dataset demonstrate SIMSplat's extensive editing capabilities and adaptability across a wide range of scenarios. Project page: https://sungyeonparkk.github.io/simsplat/

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