VG3S: Visual Geometry Grounded Gaussian Splatting for Semantic Occupancy Prediction
3D semantic occupancy prediction has become a crucial perception task for comprehensive scene understanding in autonomous driving. While recent advances have explored 3D Gaussian splatting for occupancy modeling to substantially reduce computational overhead, the generation of high-quality 3D Gaussians relies heavily on accurate geometric cues, which are often insufficient in purely vision-centric paradigms. To bridge this gap, we advocate for injecting the strong geometric grounding capability from Vision Foundation Models (VFMs) into occupancy prediction. In this regard, we introduce Visual Geometry Grounded Gaussian Splatting (VG3S), a novel framework that empowers Gaussian-based occup...
| Authors | Xiaoyang Yan, Muleilan Pei, Shaojie Shen |
|---|---|
| Primary category | cs.CV |
| Published | 6 March 2026 |
| Last updated at source | 22 July 2026 |
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