8 citations · 11 across the 4 of their papers we have counts for
4 papers
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…
Learning a Diffusion Prior for NeRFs
Guandao Yang, Abhijit Kundu, Leonidas J. Guibas +2
Neural Radiance Fields (NeRFs) have emerged as a powerful neural 3D representation for objects and scenes derived from 2D data. Generating NeRFs, however, remains difficult in many…
NeRFMeshing: Distilling Neural Radiance Fields into Geometrically-Accurate 3D Meshes
Marie-Julie Rakotosaona, Fabian Manhardt, Diego Martin Arroyo +3
With the introduction of Neural Radiance Fields (NeRFs), novel view synthesis has recently made a big leap forward. At the core, NeRF proposes that each 3D point can emit radiance,…
Nerflets: Local Radiance Fields for Efficient Structure-Aware 3D Scene Representation from 2D Supervision
Xiaoshuai Zhang, Abhijit Kundu, Thomas Funkhouser +3
We address efficient and structure-aware 3D scene representation from images. Nerflets are our key contribution -- a set of local neural radiance fields that together represent a s…