Direkt zum Inhalt springen
Computer Vision Group
TUM School of Computation, Information and Technology
Technical University of Munich

Technical University of Munich

Menu

Links

Informatik IX
Computer Vision Group

Boltzmannstrasse 3
85748 Garching info@vision.in.tum.de

Follow us on:

News

04.03.2024

We have twelve papers accepted to CVPR 2024. Check our publication page for more details.

18.07.2023

We have four papers accepted to ICCV 2023. Check out our publication page for more details.

02.03.2023

CVPR 2023

We have six papers accepted to CVPR 2023. Check out our publication page for more details.

15.10.2022

NeurIPS 2022

We have two papers accepted to NeurIPS 2022. Check out our publication page for more details.

15.10.2022

WACV 2023

We have two papers accepted at WACV 2023. Check out our publication page for more details.

More


Research Interests

Variational Methods, Continuous and Discrete Optimization, Computer Graphics, Mathematics, Statistical Methods

Brief Bio

Eno Töppe studied Computer Science at Bonn University. He received the "Vordiplom" degree in 2006 and the "Diplom" degree in 2008. His master thesis was awarded the price for the best master thesis of the year by the Bonn Society for Computer Science.
Since 2009 he is a Ph.D. student in the Research Group for Computer Vision, Image Processing and Pattern Recognition, Technical University of Munich, Germany, headed by Professor Daniel Cremers. Eno Töppe is supported by Microsoft Research, Cambridge. He is coadvised by Carsten Rother and Andrew Fitzgibbon (MSR Cambridge).

Publications

I am currently working in the following research areas:

3D Reconstruction from a Single Image. Based on a single image the silhouette of the object is extracted. By applying additional constraints e.g. on the volume of the object or the shape along cross sections 3D models can be computed from variational approaches.
Image Segmentation. Theoretical and experimental comparison of discrete and continuous optimization methods for multilabel problems.
Planar Graph Cuts. The PlanarCut library computes a max-flow/min-s-t-cut on planar graphs. It implements an efficient algorithm, which has almost linear running time. The code to the project can be downloaded.

Rechte Seite

Informatik IX
Computer Vision Group

Boltzmannstrasse 3
85748 Garching info@vision.in.tum.de

Follow us on:

News

04.03.2024

We have twelve papers accepted to CVPR 2024. Check our publication page for more details.

18.07.2023

We have four papers accepted to ICCV 2023. Check out our publication page for more details.

02.03.2023

CVPR 2023

We have six papers accepted to CVPR 2023. Check out our publication page for more details.

15.10.2022

NeurIPS 2022

We have two papers accepted to NeurIPS 2022. Check out our publication page for more details.

15.10.2022

WACV 2023

We have two papers accepted at WACV 2023. Check out our publication page for more details.

More