30 citations · 36 across the 4 of their papers we have counts for
8 papers
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…
LLM-Grounder: Open-Vocabulary 3D Visual Grounding with Large Language Model as an Agent
Jianing Yang, Xuweiyi Chen, Shengyi Qian +4
3D visual grounding is a critical skill for household robots, enabling them to navigate, manipulate objects, and answer questions based on their environment. While existing approac…
NIFTY: Neural Object Interaction Fields for Guided Human Motion Synthesis
Nilesh Kulkarni, Davis Rempe, Kyle Genova +4
We address the problem of generating realistic 3D motions of humans interacting with objects in a scene. Our key idea is to create a neural interaction field attached to a specific…
PlaneFormers: From Sparse View Planes to 3D Reconstruction
Samir Agarwala, Linyi Jin, Chris Rockwell +1
We present an approach for the planar surface reconstruction of a scene from images with limited overlap. This reconstruction task is challenging since it requires jointly reasonin…
Recognizing Scenes from Novel Viewpoints
Shengyi Qian, Alexander Kirillov, Nikhila Ravi +4
Humans can perceive scenes in 3D from a handful of 2D views. For AI agents, the ability to recognize a scene from any viewpoint given only a few images enables them to efficiently…