SeeGround localizes objects in 3D scenes from natural language without 3D-specific training, using query-aligned rendered views and spatially enriched text fed to a 2D vision-language model.
Deep view synthesis via self-consistent gen- erative network,
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
citation-role summary
background 1
citation-polarity summary
fields
cs.CV 1years
2025 1verdicts
CONDITIONAL 1roles
background 1polarities
background 1representative citing papers
citing papers explorer
-
Zero-Shot 3D Visual Grounding from Vision-Language Models
SeeGround localizes objects in 3D scenes from natural language without 3D-specific training, using query-aligned rendered views and spatially enriched text fed to a 2D vision-language model.