Matching of Deformable Shapes with Topological Noise. - Zorah Lähner; Emanuele Rodolà; Michael M. Bronstein; Daniel Cremers; Oliver Burghard; Luca Cosmo; Alexander Dieckmann; Reinhard Klein; Yusuf Sahillioglu (3DOR@Eurographics, 2016)

Efficient Globally Optimal 2D-to-3D Deformable Shape Matching. - Zorah Lähner; Emanuele Rodolà; Frank R. Schmidt; Michael M. Bronstein; Daniel Cremers (CVPR, 2016)

Efficient Deformable Shape Correspondence via Kernel Matching. - Matthias Vestner; Zorah Lähner; Amit Boyarski; Or Litany; Ron Slossberg; Tal Remez; Emanuele Rodolà; Alexander M. Bronstein; Michael M. Bronstein; Ron Kimmel; Daniel Cremers (3DV, 2017)

DeepWrinkles: Accurate and Realistic Clothing Modeling. - Zorah Lähner; Daniel Cremers; Tony Tung (ECCV (4), 2018)

Functional Maps on Product Manifolds. - Emanuele Rodolà; Zorah Lähner; Alex M. Bronstein; Michael M. Bronstein; Justin Solomon 001 (SGP (Posters), 2018)

Divergence-Free Shape Interpolation and Correspondence. - Marvin Eisenberger; Zorah Lähner; Daniel Cremers (CoRR, 2018)

Shape Correspondence with Isometric and Non-Isometric Deformations. - Roberto M. Dyke; C. Stride; Yu-Kun Lai; Paul L. Rosin; Mathieu Aubry; Amit Boyarski; Alexander M. Bronstein; Michael M. Bronstein; Daniel Cremers; Matthew Fisher; Thibault Groueix; Daoliang Guo; et al. (3DOR@Eurographics, 2019)

Divergence-Free Shape Correspondence by Deformation. - Marvin Eisenberger; Zorah Lähner; Daniel Cremers (Comput. Graph. Forum, 2019)

Functional Maps Representation On Product Manifolds. - Emanuele Rodolà; Zorah Lähner; Alexander M. Bronstein; Michael M. Bronstein; Justin Solomon 001 (Comput. Graph. Forum, 2019)

Unsupervised Dense Shape Correspondence using Heat Kernels. - Mehmet Aygün; Zorah Lähner; Daniel Cremers (3DV, 2020)

Simulated Annealing for 3D Shape Correspondence. - Benjamin Holzschuh; Zorah Lähner; Daniel Cremers (3DV, 2020)

Smooth Shells: Multi-Scale Shape Registration With Functional Maps. - Marvin Eisenberger; Zorah Lähner; Daniel Cremers (CVPR, 2020)

Isometric Multi-Shape Matching. - Maolin Gao; Zorah Lähner; Johan Thunberg; Daniel Cremers; Florian Bernard (CVPR, 2021)

Q-Match: Iterative Shape Matching via Quantum Annealing. - Marcel Seelbach Benkner; Zorah Lähner; Vladislav Golyanik; Christof Wunderlich; Christian Theobalt; Michael Moeller 001 (ICCV, 2021)

Training or Architecture? How to Incorporate Invariance in Neural Networks. - Kanchana Vaishnavi Gandikota; Jonas Geiping; Zorah Lähner; Adam Czaplinski; Michael Möller 001 (CoRR, 2021)

Continuous Correspondence of Non-Rigid 3D Shapes. - Zorah Lähner (2021)

A Simple Strategy to Provable Invariance via Orbit Mapping. - Kanchana Vaishnavi Gandikota; Jonas Geiping; Zorah Lähner; Adam Czaplinski; Michael Möller 001 (ACCV (5), 2022)

Intrinsic Neural Fields: Learning Functions on Manifolds. - Lukas Koestler; Daniel Grittner; Michael Möller 001; Daniel Cremers; Zorah Lähner (ECCV (2), 2022)

CCuantuMM: Cycle-Consistent Quantum-Hybrid Matching of Multiple Shapes. - Harshil Bhatia; Edith Tretschk; Zorah Lähner; Marcel Seelbach Benkner; Michael Moeller 001; Christian Theobalt; Vladislav Golyanik (CVPR, 2023)

Conjugate Product Graphs for Globally Optimal 2D-3D Shape Matching. - Paul Roetzer; Zorah Lähner; Florian Bernard (CVPR, 2023)

A Network Analysis for Correspondence Learning via Linearly-Embedded Functions. - Sharik Siddiqi; Zorah Lähner (DAGM, 2023)

ΣIGMA: Scale-Invariant Global Sparse Shape Matching. - Maolin Gao; Paul Roetzer; Marvin Eisenberger; Zorah Lähner; Michael Möller 001; Daniel Cremers; Florian Bernard (ICCV, 2023)

QuAnt: Quantum Annealing with Learnt Couplings. - Marcel Seelbach Benkner; Maximilian Krahn; Edith Tretschk; Zorah Lähner; Michael Moeller 001; Vladislav Golyanik (ICLR, 2023)

Kissing to Find a Match: Efficient Low-Rank Permutation Representation. - Hannah Dröge; Zorah Lähner; Yuval Bahat; Onofre Martorell Nadal; Felix Heide; Michael Moeller 001 (NeurIPS, 2023)

On the Direct Alignment of Latent Spaces. - Zorah Lähner; Michael Moeller 001 (UniReps, 2023)

SIGMA: Scale-Invariant Global Sparse Shape Matching. - Maolin Gao; Paul Roetzer; Marvin Eisenberger; Zorah Lähner; Michael Möller 001; Daniel Cremers; Florian Bernard (CoRR, 2023)

Kissing to Find a Match: Efficient Low-Rank Permutation Representation. - Hannah Dröge; Zorah Lähner; Yuval Bahat; Onofre Martorell; Felix Heide; Michael Möller 001 (CoRR, 2023)

Hybrid Functional Maps for Crease-Aware Non-Isometric Shape Matching. - Lennart Bastian; Yizheng Xie; Nassir Navab; Zorah Lähner (CVPR, 2024)

Synchronous Diffusion for Unsupervised Smooth Non-rigid 3D Shape Matching. - Dongliang Cao; Zorah Lähner; Florian Bernard (ECCV (5), 2024)

Implicit-ARAP: Efficient Handle-Guided Deformation of High-Resolution Meshes and Neural Fields via Local Patch Meshing. - Daniele Baieri; Filippo Maggioli; Zorah Lähner; Simone Melzi; Emanuele Rodolà (CoRR, 2024)

SShaDe: scalable shape deformation via local representations. - Filippo Maggioli; Daniele Baieri; Zorah Lähner; Simone Melzi (CoRR, 2024)

3D Shape Completion with Test-Time Training. - Michael Schopf-Kuester; Zorah Lähner; Michael Möller 001 (CoRR, 2024)

Beyond Complete Shapes: A Quantitative Evaluation of 3D Shape Matching Algorithms. - Viktoria Ehm; Nafie El Amrani; Yizheng Xie; Lennart Bastian; Maolin Gao; Weikang Wang 004; Lu Sang; Dongliang Cao; Zorah Lähner; Daniel Cremers; Florian Bernard (CoRR, 2024)

Higher-Order Ratio Cycles for Fast and Globally Optimal Shape Matching. - Paul Roetzer; Viktoria Ehm; Daniel Cremers; Zorah Lähner; Florian Bernard (CVPR, 2025)

Denoising Functional Maps: Diffusion Models for Shape Correspondence. - Aleksei Zhuravlev; Zorah Lähner; Vladislav Golyanik (CVPR, 2025)

Preface of UniReps: the Second Edition of the Workshop on Unifying Representations in Neural Models. - Clémentine Dominé; Marco Fumero; Zorah Lähner; Donato Crisostomi; Luca Moschella; Kimberly Stachenfeld (UniReps, 2025)

Laplace-Beltrami Operator for Gaussian Splatting. - Hongyu Zhou; Zorah Lähner (CoRR, 2025)