25 citations · 29 across the 7 of their papers we have counts for
8 papers · 1 filter
TokenMatch: 3D Mesh Correspondence Transformer with Curvature-Guided Tokenisation
Adeela Islam, Zorah Lähner, Vittorio Murino +1
While data-driven 3D shape correspondence estimation has recently seen substantial progress, robust matching under partial observations and strong non-isometric deformations remain…
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…
Q-Match: Iterative Shape Matching via Quantum Annealing
Marcel Seelbach Benkner, Zorah Lähner, Vladislav Golyanik +3
Finding shape correspondences can be formulated as an NP-hard quadratic assignment problem (QAP) that becomes infeasible for shapes with high sampling density. A promising research…
Unsupervised Dense Shape Correspondence using Heat Kernels
Mehmet Aygün, Zorah Lähner, Daniel Cremers
In this work, we propose an unsupervised method for learning dense correspondences between shapes using a recent deep functional map framework. Instead of depending on ground-truth…