Geometric Deep Learning

Research Grants

KI-Starter from the Ministry for Culture and Science NRW ‘Robust Geometric Deep Learning’ (2022-2024)

Publications

Kissing to Find a Match: Efficient Low-Rank Permutation Representation

Hannah Dröge, Zorah Lähner, Yuval Bahat, Onofre Martorell, Felix Heide, Michael Moeller
Published in arXiv, 2023
[arxiv] [bibtex]

A Network Analysis for Correspondence Learning via Linearly-Embedded Functions

Sharik Siddiqi, Zorah Lähner
Published in Accepted to German Conference on Pattern Recognition (GCPR), 2023
[bibtex]

A Simple Strategy to Make Neural Networks Provably Invariant

Kanchana Vaishnavi Gandikota, Jonas Geiping, Zorah Lähner, Adam Czapliński, Michael Moeller
Published in Asian Conference on Computer Vision (ACCV), 2022
[pdf] [arxiv] [bibtex]

Intrinsic Neural Fields: Learning Functions on Manifolds

Lukas Koestler, Daniel Grittner, Michael Moeller, Daniel Cremers, Zorah Lähner
Published in European Conference on Computer Vision (ECCV), 2022
[pdf] [arxiv] [github] [bibtex]

Unsupervised Dense Shape Correspondence using Heat Kernels

Mehmet Aygün, Zorah Lähner, Daniel Cremers
Published in Conference on 3D Vision (3DV), 2020
[pdf] [arxiv] [bibtex]

DeepWrinkles: Accurate and Realistic Clothing Modeling

Zorah Lähner, Daniel Cremers, Tony Tung
Published in European Conference on Computer Vision (ECCV), 2018
[pdf] [arxiv] [video] [bibtex]