1 citations · 1 across the 2 of their papers we have counts for
5 papers
Radiance Meshes for Volumetric Reconstruction
Alexander Mai, Trevor Hedstrom, George Kopanas +3
We introduce radiance meshes, a technique for representing radiance fields with constant density tetrahedral cells produced with a Delaunay tetrahedralization. Unlike a Voronoi dia…
MoMaps: Semantics-Aware Scene Motion Generation with Motion Maps
Jiahui Lei, Kyle Genova, George Kopanas +2
This paper addresses the challenge of learning semantically and functionally meaningful 3D motion priors from real-world videos, in order to enable prediction of future 3D scene mo…
StochasticSplats: Stochastic Rasterization for Sorting-Free 3D Gaussian Splatting
Shakiba Kheradmand, Delio Vicini, George Kopanas +4
3D Gaussian splatting (3DGS) is a popular radiance field method, with many application-specific extensions. Most variants rely on the same core algorithm: depth-sorting of Gaussian…
Does 3D Gaussian Splatting Need Accurate Volumetric Rendering?
Adam Celarek, George Kopanas, George Drettakis +2
Since its introduction, 3D Gaussian Splatting (3DGS) has become an important reference method for learning 3D representations of a captured scene, allowing real-time novel-view syn…
Synthetic Prior for Few-Shot Drivable Head Avatar Inversion
Wojciech Zielonka, Stephan J. Garbin, Alexandros Lattas +5
We present SynShot, a novel method for the few-shot inversion of a drivable head avatar based on a synthetic prior. We tackle three major challenges. First, training a controllable…