MotionGS-SLAM: Event-Modulated Gaussian Splatting for Motion-Blur Robust SLAM
Current Vision-based SLAM systems fail catastrophically when motion blur corrupts the visual input, as they attempt the ill-posed inverse problem of recovering sharp content from degraded observations. We present MotionGS-SLAM, which fundamentally reimagines motion blur handling through a paradigm shift: rather than removing blur artifacts, we reformulate the challenge as a well-constrained forward problem that generatively models blur formation within the rendering pipeline. By leveraging event cameras' microsecond temporal resolution and immunity to motion blur, we introduce a novel event-modulated Gaussian kernel that dynamically adapts each Gaussian's rasterization based on precise mo...
| Authors | Zhiqiang Hu, Shouren Huang, Masatoshi Ishikawa |
|---|---|
| Primary category | cs.RO |
| Published | 15 August 2026 |
| Last updated at source | 15 August 2026 |
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