Flow4DGS-SLAM: Optical Flow-Guided 4D Gaussian Splatting SLAM
Handling the dynamic environments is a significant research challenge in Visual Simultaneous Localization and Mapping (SLAM). Recent research combines 3D Gaussian Splatting (3DGS) with SLAM to achieve both robust camera pose estimation and photorealistic renderings. However, using SLAM to efficiently reconstruct both static and dynamic regions remains challenging. In this work, we propose an efficient framework for dynamic 3DGS SLAM guided by optical flow. Using the input depth and prior optical flow, we first propose a category-agnostic motion mask generation strategy by fitting a camera ego-motion model to decompose the optical flow. This module separates dynamic and static Gaussians an...
| Authors | Yunsong Wang, Gim Hee Lee |
|---|---|
| Primary category | cs.CV |
| Published | 24 April 2026 |
| Last updated at source | 28 April 2026 |
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