6 citations · 6 across the 2 of their papers we have counts for
3 papers
Locate 3D: Real-World Object Localization via Self-Supervised Learning in 3D
Sergio Arnaud, Paul McVay, Ada Martin +19
We present LOCATE 3D, a model for localizing objects in 3D scenes from referring expressions like "the small coffee table between the sofa and the lamp." LOCATE 3D sets a new state…
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…
Beyond A*: Better Planning with Transformers via Search Dynamics Bootstrapping
Lucas Lehnert, Sainbayar Sukhbaatar, DiJia Su +4
While Transformers have enabled tremendous progress in various application settings, such architectures still trail behind traditional symbolic planners for solving complex decisio…