VEOcc: Voxel-Centric Online Semantic Occupancy Prediction For Embodied Scene Understanding
Crucial for autonomous exploration, online 3D occupancy prediction and mapping incrementally construct dense spatial representations on the fly. Embodied online occupancy prediction remains predominantly Gaussian-centric, despite the wide use of voxel representations for frame-wise scene completion. We present VEOcc, to the best of our knowledge, the first voxel-centric framework for online embodied semantic occupancy prediction. It incrementally maintains a sparse global semantic voxel map from monocular observations and enables open-ended expansion without predefined scene bounds. To robustly integrate noisy multi-view predictions, we further introduce a Spatio-Temporal-Aware Online Upd...
| Authors | Ruoyu Wang, Yong Liu, Jiahan Li et al. |
|---|---|
| Primary category | cs.CV |
| Published | 24 May 2026 |
| Last updated at source | 22 September 2026 |
Silytics shows public metadata from arXiv and links to the original. Information may be incomplete or out of date. Last refreshed 17 October 2026. Licenses and terms of the original apply to the work itself. Not financial, legal or professional advice.