Chair for Machine Learning & Computer Vision

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  3. Faculty of Applied Computer Science
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  8. Robin Schön

Robin Schön

Research Assistant & PhD Student
Chair for Machine Learning & Computer Vision
Phone: +49 (821) 598 4368
Email: robin.schoen@informatik.uni-augsburg.de
Room: 1012 (N)
Visiting hours: by appointment
Address: Universitätsstraße 6a, 86159 Augsburg

Research Interest

  • Image-to-Image Translation
  • Semantic Segmentation
  • Domain Adaptation

Publications

Schön, Robin
2022 | 2021

2022

Daniel Kienzle, Julian Lorenz, Robin Schön, Katja Ludwig and Rainer Lienhart. 2022. COVID detection and severity prediction with 3D-ConvNeXt and custom pretrainings. In Computer Vision - ECCV 2022 proceedings: 17th European Conference, Tel Aviv, Israel, October 23–27, 2022. , arXiv:2206.15073 DOI: 10.48550/arXiv.2206.15073
PDF | BibTeX | RIS | DOI

Sebastian Scherer, Robin Schön and Rainer Lienhart. in press. Pseudo-label noise suppression techniques for semi-supervised semantic segmentation. .
PDF | BibTeX | RIS | URL

2021

Robin Schön. 2021. Learning semantic segmentation from synthetic data using generative adversarial networks. Masterarbeit, Universität Augsburg.
BibTeX | RIS

Sebastian Scherer, Robin Schön, Katja Ludwig and Rainer Lienhart. 2021. Unsupervised domain extension for nighttime semantic segmentation in urban scenes. In Ana Fred, Carlo Sansone and Kurosh Madani (Ed.). Proceedings of the 2nd International Conference on Deep Learning Theory and Applications (DeLTA 2021). SciTePress, Setúbal, 38-47. DOI: 10.5220/0010551500380047
PDF | BibTeX | RIS | DOI

Abschlussarbeiten

Robin Schön. Learning Semantic Segmentation from Synthetic Data using Generative Adversarial Networks.  Masters Thesis, January 2021.

Lehre

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