25 citations · 36 across the 15 of their papers we have counts for
19 papers
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…
Towards Stellarator Geometry Optimisation for Nuclear Fusion
Tobias Weißberg, Moritz Heep, Zorah Lähner +1
We present a local geometry refinement method and a 2D latent representation that took us to the top of the ConStellaration leaderboard on the geometric task in May 2026.
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…
Geometry Gaussians: Decoupling Appearance and Geometry in Gaussian Splatting
Hongyu Zhou, Zorah Lähner
After the success of 3D Gaussian Splatting (3DGS) for novel view synthesis, many works have explored how to also use it for geometric surface representation. However, extracting ac…
MoAngelo: Motion-Aware Neural Surface Reconstruction for Dynamic Scenes
Mohamed Ebbed, Zorah Lähner
Dynamic scene reconstruction from multi-view videos remains a fundamental challenge in computer vision. While recent neural surface reconstruction methods have achieved remarkable…
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…
Laplace-Beltrami Operator for Gaussian Splatting
Hongyu Zhou, Zorah Lähner
With the rising popularity of 3D Gaussian splatting and the expanse of applications from rendering to 3D reconstruction, there comes also a need for geometry processing application…
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…
CCuantuMM: Cycle-Consistent Quantum-Hybrid Matching of Multiple Shapes
Harshil Bhatia, Edith Tretschk, Zorah Lähner +4
Jointly matching multiple, non-rigidly deformed 3D shapes is a challenging, -hard problem. A perfect matching is necessarily cycle-consistent: Following the pairwise…
Conjugate Product Graphs for Globally Optimal 2D-3D Shape Matching
Paul Roetzer, Zorah Lähner, Florian Bernard
We consider the problem of finding a continuous and non-rigid matching between a 2D contour and a 3D mesh. While such problems can be solved to global optimality by finding a short…
QuAnt: Quantum Annealing with Learnt Couplings
Marcel Seelbach Benkner, Maximilian Krahn, Edith Tretschk +3
Modern quantum annealers can find high-quality solutions to combinatorial optimisation objectives given as quadratic unconstrained binary optimisation (QUBO) problems. Unfortunatel…
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…
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…
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…
Functional Maps Representation on Product Manifolds
Emanuele Rodolà, Zorah Lähner, Alex M. Bronstein +2
We consider the tasks of representing, analyzing and manipulating maps between shapes. We model maps as densities over the product manifold of the input shapes; these densities can…
Divergence-Free Shape Interpolation and Correspondence
Marvin Eisenberger, Zorah Lähner, Daniel Cremers
We present a novel method to model and calculate deformation fields between shapes embedded in . Our framework combines naturally interpolating the two input shapes a…
Efficient Deformable Shape Correspondence via Kernel Matching
Zorah Lähner, Matthias Vestner, Amit Boyarski +8
We present a method to match three dimensional shapes under non-isometric deformations, topology changes and partiality. We formulate the problem as matching between a set of pair-…