7 citations · 8 across the 14 of their papers we have counts for
4 papers · 1 filter
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…
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…
3DFIRES: Few Image 3D REconstruction for Scenes with Hidden Surface
Linyi Jin, Nilesh Kulkarni, David Fouhey
This paper introduces 3DFIRES, a novel system for scene-level 3D reconstruction from posed images. Designed to work with as few as one view, 3DFIRES reconstructs the complete geome…
FAR: Flexible, Accurate and Robust 6DoF Relative Camera Pose Estimation
Chris Rockwell, Nilesh Kulkarni, Linyi Jin +3
Estimating relative camera poses between images has been a central problem in computer vision. Methods that find correspondences and solve for the fundamental matrix offer high pre…