6 papers · 1 filter
Confidence matters: Leveraging Multi-view Geometric Priors for GS-based Reconstruction
Hongyu Zhou, Zorah Lähner
3D Gaussian splatting (3DGS) has emerged as a widely-used tool for novel view synthesis, offering real-time rendering in a sparse representation. However, the method's reliance on…
Denoising Functional Maps: Diffusion Models for Shape Correspondence
Aleksei Zhuravlev, Zorah Lähner, Vladislav Golyanik
Estimating correspondences between pairs of deformable shapes remains a challenging problem. Despite substantial progress, existing methods lack broad generalization capabilities a…
3D Shape Completion with Test-Time Training
Michael Schopf-Kuester, Zorah Lähner, Michael Moeller
This work addresses the problem of \textit{shape completion}, i.e., the task of restoring incomplete shapes by predicting their missing parts. While previous works have often predi…
Hybrid Functional Maps for Crease-Aware Non-Isometric Shape Matching
Lennart Bastian, Yizheng Xie, Nassir Navab +1
Non-isometric shape correspondence remains a fundamental challenge in computer vision. Traditional methods using Laplace-Beltrami operator (LBO) eigenmodes face limitations in char…
SIGMA: Scale-Invariant Global Sparse Shape Matching
Maolin Gao, Paul Roetzer, Marvin Eisenberger +4
We propose a novel mixed-integer programming (MIP) formulation for generating precise sparse correspondences for highly non-rigid shapes. To this end, we introduce a projected Lapl…
Isometric Multi-Shape Matching
Maolin Gao, Zorah Lähner, Johan Thunberg +2
Finding correspondences between shapes is a fundamental problem in computer vision and graphics, which is relevant for many applications, including 3D reconstruction, object tracki…