3 papers
cs.CV2026
Modality Forcing for Scalable Spatial Generation
Bardienus Pieter Duisterhof, Deva Ramanan, Jeffrey Ichnowski +2
Text-to-image (T2I) models contain rich spatial priors. Synthesizing photorealistic, cluttered scenes requires an understanding of geometry, including perspective and relative scal…
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…
cs.CV2024
Lightplane: Highly-Scalable Components for Neural 3D Fields
Ang Cao, Justin Johnson, Andrea Vedaldi +1
Contemporary 3D research, particularly in reconstruction and generation, heavily relies on 2D images for inputs or supervision. However, current designs for these 2D-3D mapping are…