3 papers
cs.CV2025
Neural USD: An object-centric framework for iterative editing and control
Alejandro Escontrela, Shrinu Kushagra, Sjoerd van Steenkiste +5
Amazing progress has been made in controllable generative modeling, especially over the last few years. However, some challenges remain. One of them is precise and iterative object…
cs.CV2024
MegaSaM: Accurate, Fast, and Robust Structure and Motion from Casual Dynamic Videos
Zhengqi Li, Richard Tucker, Forrester Cole +6
We present a system that allows for accurate, fast, and robust estimation of camera parameters and depth maps from casual monocular videos of dynamic scenes. Most conventional stru…
cs.CV2024
Stereo4D: Learning How Things Move in 3D from Internet Stereo Videos
Linyi Jin, Richard Tucker, Zhengqi Li +3
Learning to understand dynamic 3D scenes from imagery is crucial for applications ranging from robotics to scene reconstruction. Yet, unlike other problems where large-scale superv…