PruneGround: Plug-and-play Spatial Pruning for 3D Visual Grounding
Quick summary
arXiv:2606.31148v2 Announce Type: replace-cross Abstract: 3D Visual Grounding (3DVG) aims to localize target objects in 3D scenes given natural language descriptions. Existing approaches typically perform reasoning over the entire scene, leading to ambiguous predictions and high computational cost, especially in cluttered environments. We observe that many referential expressions rely on local spatial context and often correspond to restricted spatial regions rather than the full scene. Motivated by this insight, we propose PruneGround, an effective plug-and-play framework for 3DVG built upon
Key takeaways
- arXiv:2606.31148v2 Announce Type: replace-cross Abstract: 3D Visual Grounding (3DVG) aims to localize target objects in 3D scenes given natural language descriptions.
- Existing approaches typically perform reasoning over the entire scene, leading to ambiguous predictions and high computational cost, especially in cluttered environments.
- We observe that many referential expressions rely on local spatial context and often correspond to restricted spatial regions rather than the full scene.
Why it matters
“PruneGround: Plug-and-play Spatial Pruning for 3D Visual Grounding” should be evaluated beyond branding and benchmark scores. Its practical importance will emerge in task accuracy, latency, unit cost, safety and integration with real workflows.
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