1 citations · 1 across the 10 of their papers we have counts for
12 papers
Meshtryoshka: Differentiable Rendering of Real-World Scenes via Mesh Rasterization
David Charatan, Daniel Xu, Richard Szeliski +2
Differentiable rendering has emerged as a powerful approach for 3D reconstruction and novel view synthesis. State-of-the-art differentiable rendering methods combine a variety of c…
Lighting-Consistent Object Transfer Across Radiance Fields
Nicolás Violante, George Kopanas, Linus Franke +2
3D Gaussian Splatting (3DGS) is widely used to capture and render real scenes. Compositing objects from one capture into another has applications in many domains, such as VFX, arch…
Eulerian Gaussian Splatting using Hashed Probability Pyramids
Mia Gaia Polansky, George Kopanas, Stephan Garbin +2
We introduce a probabilistic splat-based radiance field framework that retains the fast rasterization and test-time efficiency of 3D Gaussian Splatting (3DGS) while replacing heuri…
Exploiting the Degrees of Freedom: Multi-Dimensional Spatially-Coupled Codes Based on Gradient Descent
Ata Tanrıkulu, Mete Yıldırım, Ahmed Hareedy
Spatially-coupled (SC) codes are a class of low-density parity-check (LDPC) codes that is gaining increasing attention. Multi-dimensional (MD) SC codes are constructed by connectin…
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…
Generative View Stitching
Chonghyuk Song, Michal Stary, Boyuan Chen +2
Autoregressive video diffusion models are capable of long rollouts that are stable and consistent with history, but they are unable to guide the current generation with conditionin…
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…
EVER: Exact Volumetric Ellipsoid Rendering for Real-time View Synthesis
Alexander Mai, Peter Hedman, George Kopanas +6
We present Exact Volumetric Ellipsoid Rendering (EVER), a method for real-time differentiable emission-only volume rendering. Unlike recent rasterization based approach by 3D Gauss…
SpotlessSplats: Ignoring Distractors in 3D Gaussian Splatting
Sara Sabour, Lily Goli, George Kopanas +6
3D Gaussian Splatting (3DGS) is a promising technique for 3D reconstruction, offering efficient training and rendering speeds, making it suitable for real-time applications.However…