UnsOcc proposes RenderFusion and GSRefinement to improve 3D semantic occupancy prediction in unstructured scenes by enhancing cross-modal fusion and long-tail supervision, outperforming SOTA on a new mine dataset and nuScenes.
L2cocc: Lightweight camera-centric semantic scene completion via distillation of lidar model,
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
fields
cs.CV 1years
2026 1verdicts
UNVERDICTED 1representative citing papers
citing papers explorer
-
UnsOcc: 3D Semantic Occupancy Prediction in Unstructured Scene via Rendering Fusion
UnsOcc proposes RenderFusion and GSRefinement to improve 3D semantic occupancy prediction in unstructured scenes by enhancing cross-modal fusion and long-tail supervision, outperforming SOTA on a new mine dataset and nuScenes.