3 papers
cs.CV2026
SAM 3D: 3Dfy Anything in Images
SAM 3D Team, Xingyu Chen, Fu-Jen Chu +20
We present SAM 3D, a generative model for visually grounded 3D object reconstruction, predicting geometry, texture, and layout from a single image. SAM 3D excels in natural images,…
cs.CV2025
Error-Driven Scene Editing for 3D Grounding in Large Language Models
Yue Zhang, Zun Wang, Han Lin +5
Despite recent progress in 3D-LLMs, they remain limited in accurately grounding language to visual and spatial elements in 3D environments. This limitation stems in part from train…
cs.CV2025
From Thousands to Billions: 3D Visual Language Grounding via Render-Supervised Distillation from 2D VLMs
Ang Cao, Sergio Arnaud, Oleksandr Maksymets +12
3D vision-language grounding faces a fundamental data bottleneck: while 2D models train on billions of images, 3D models have access to only thousands of labeled scenes--a six-orde…