Technical University of Munich

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Marvin Eisenberger

AlumniTechnical University of Munich

School of Computation, Information and Technology
Informatics 9
Boltzmannstrasse 3
85748 Garching
Germany

Fax: +49-89-289-17757
Office:
Mail: marvin.eisenberger@in.tum.de

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Preprints

2022
[]		Implicit Shape Completion via Adversarial Shape Priors (A Saroha, M Eisenberger, T Yenamandra and D Cremers), In arXiv preprint arXiv:2204.10060, 2022. [bibtex]

Conference and Workshop Papers
2024
[]		Partial-to-Partial Shape Matching with Geometric Consistency (V Ehm, M Gao, P Roetzer, M Eisenberger, D Cremers and F Bernard), In IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2024. ([webpage]) [bibtex]
[]		SatSynth: Augmenting Image-Mask Pairs through Diffusion Models for Aerial Semantic Segmentation (A Toker, M Eisenberger, D Cremers and L Leal-Taixe), In IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2024. [bibtex]
[]		Spectral Meets Spatial: Harmonising 3D Shape Matching and Interpolation (D Cao, M Eisenberger, N El Amrani, D Cremers and F Bernard), In IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2024. [bibtex]
[]		Geometrically Consistent Partial Shape Matching (V Ehm, P Roetzer, M Eisenberger, M Gao, F Bernard and D Cremers), In 3DV, 2024. [bibtex]
2023
[]		SIGMA: Quantum Scale-Invariant Global Sparse Shape Matching (M Gao, P Roetzer, M Eisenberger, Z Lähner, M Moeller, D Cremers and F Bernard), In International Conference on Computer Vision (ICCV), 2023. ([pdf]) [bibtex]
[]		ResolvNet: A Graph Convolutional Network with multi-scale Consistency (C Koke, A Saroha, Y Shen, M Eisenberger and D Cremers), In NeurIPS 2023 Workshop: New Frontiers in Graph Learning, 2023. [bibtex] [arXiv:2310.00431]Oral Presentation
[]		G-MSM: Unsupervised Multi-Shape Matching with Graph-based Affinity Priors (M. Eisenberger, A. Toker, L. Leal-Taixé and D. Cremers), In IEEE International Conference on Computer Vision and Pattern Recognition (CVPR), 2023. ([arXiv] [code]) [bibtex]
2022
[]		A Unified Framework for Implicit Sinkhorn Differentiation (M. Eisenberger, A. Toker, L. Leal-Taixé, F. Bernard and D. Cremers), In IEEE International Conference on Computer Vision and Pattern Recognition (CVPR), 2022. ([arXiv] [code]) [bibtex]
[]		DynamicEarthNet: Daily Multi-Spectral Satellite Dataset for Semantic Change Segmentation (A Toker, L Kondmann, M Weber, M Eisenberger, C Andres, J Hu, A Hoderlein, C Senaras, T Davis, D Cremers, G Marchisio, X Zhu and L Leal-Taixe), In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022. [bibtex] [pdf]
2021
[]		NeuroMorph: Unsupervised Shape Interpolation and Correspondence in One Go (M. Eisenberger, D. Novotny, G. Kerchenbaum, P. Labatut, N. Neverova, D. Cremers and A. Vedaldi), In IEEE International Conference on Computer Vision and Pattern Recognition (CVPR), 2021. ([arXiv] [code]) [bibtex]
2020
[]		Deep Shells: Unsupervised Shape Correspondence with Optimal Transport (M. Eisenberger, A. Toker, L. Leal-Taixé and D. Cremers), In 34th Conference on Neural Information Processing Systems (NeurIPS), 2020. ([arXiv] [code]) [bibtex]
[]		Hamiltonian Dynamics for Real-World Shape Interpolation (M. Eisenberger and D. Cremers), In European Conference on Computer Vision (ECCV), 2020. ([arXiv] [code]) [bibtex]Spotlight Presentation
[]		Smooth Shells: Multi-Scale Shape Registration with Functional Maps (M. Eisenberger, Z. Lähner and D. Cremers), In IEEE International Conference on Computer Vision and Pattern Recognition (CVPR), 2020. ([pdf] [arXiv] [code]) [bibtex]Oral Presentation
2019
[]		Divergence-Free Shape Correspondence by Deformation (M. Eisenberger, Z. Lähner and D. Cremers), In Computer Graphics Forum, volume 38, 2019. ([arxiv]) [bibtex] [pdf]