Prof. Dr.-Ing. Margret Keuper

I joined the Data and Web Science Group in October 2023 as a Professor for Machine Learning. Since November 2021, I am also affiliated with the Max-Planck-Institute for Informatics in Saarbrücken. I joined ELLIS as a member in 2022 and as a fellow in 2024. Since 2024, I am a member of the ELLIS Unit Saarbrücken. My research interests are Computer Vision and Machine Learning. More specifically, I am interested in problems such as

• Robustness and Reliability of Deep Learning Models
• Neural Architecture Search
• Grouping Problems (in applications such as Image and Motion Segmentation and Multiple Object Tracking)
• Efficient Solvers for Large Grouping Problems
• Motion Estimation
• Image Generation and Deep Fake Detection

Before joining the University of Mannheim in 2023, I was a Professor for Visual Computing at the University of Siegen (2021–2023) and a Juniorprofessor for Image Processing (2017–2021) here in Mannheim. I did my PhD with Thomas Brox at the University of Freiburg.

Learning to Sense  – DFG Reseach Unit

Climate Visions – Automated Image Analysis for Reactions and Emotions in Images on Climate Change posted on Social Media  – funded by the BMBF (Federal Ministry of Education and Research)

TrackOpt – Learning to Optimize Physically Constrained Sparse-to-Dense Point Tracking – funded by the BMBF (Federal Ministry of Education and Research)

Previous Projects:

DeToL – Deep Topology Learning - funded by the BMBF (Federal Ministry of Education and Research)

Video Segmentation from Multiple Representations using Lifted Multicuts - DFG Project KE 2264/1–1

We are teaching the following courses:

Higher Level Computer Vision (CS 646)

Image Processing (CS 647)

Generative Computer Vision (CS 668)

Reinforcement Learning (IE 695)

Seminar: Computer Vision (CS 717) 

If you are interested in writing a seminar, Bachelor or Master thesis with us, please read the following guidelines.

Administration

• Head of examination board: Mannheim Master in Data Science (since 2024)
• Member of examination board: MSc Business Informatics (since 2025), 

• Steffen Jung
• Shashank Agnihotri
• Tejaswini Medi
• Katharina Prasse
• Mishal Fatima

External PhD Students:

• Yushi Liu (Bosch BCAI)
• Yuxuan Zhou (CISPA)
• Julia Grabinski (Fraunhofer ITWM)
• Kai Bäuerle
• Abay Artykbayev (BCAI)

Alumni:

• Yumeng Li (Bosch BCAI)
• Patrick Müller
• Amrutha Saseendran (Bosch BCAI)
• Jovita Lukasik
• Amirhossein Kardoost
• Kalun Ho (Fraunhofer ITWM)

Program Chair at GCPR 2025, Freiburg, Germany. 

Tutorial Chair at ECAI 2024 in Santiago de Compostella, Spain. 

Co-organization of the LWDA 2018 conference (Lernen. Wissen. Daten. Analysen) in Mannheim.

Recent Journal Papers

• An evaluation of zero-cost proxies-from neural architecture performance prediction to model robustness, J. Lukasik, M. Moeller, M. Keuper, International Journal of Computer Vision, 1--18, 2025.
• Learning the essential in less than 2k additional weights – a simple approach to improve image classification stability under corruptions, K. Bäuerle, P. Müller, S. M. Kazim, I. Ihrke, and M. Keuper, Transactions on Machine Learning Research, 2024.
• As large as it gets: Learning infinitely large Filters via Neural Implicit Frequency Functions, J. Grabinski, J. Keuper, M. Keuper, Transactions on Machine Learning Research 2024. (featured certification)
• Intra-& extra-source exemplar-based style synthesis for improved domain generalization, Y. Li, D. Zhang, M. Keuper, A. Khoreva, International Journal of Computer Vision, 132 (2), 446–465, 2024.
• Improving Native CNN Robustness with Filter Frequency Regularization, J. Lukasik, P. Gavrikov, J. Keuper, M. Keuper, Transactions on Machine Learning Research 2023.
• Improving primary-vertex reconstruction with a minimum-cost lifted multicut graph partitioning algorithm, V. Kostyukhin, M. Keuper, I. Ibragimov, N. Owtscharenko, M. Cristinziani, Journal of Instrumentation (JINST), Volume 18, July 2023.
• Higher-Order Multicuts for Geometric Model Fitting and Motion Segmentation, E. Levinkov*, A. Kardoost*, B. Andres and M. Keuper (*equal contribution), IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), vol. 45, no. 1, pp. 608–622, 1 Jan. 2023.
• Aliasing and adversarial robust generalization of CNNs, J. Grabinski, J. Keuper, M. Keuper, Machine Learning, Springer 2022.
• Arrow R-CNN for Handwritten Diagram Recognition, B. Schäfer, M. Keuper, H. Stuckenschmidt, International Journal on Document Analysis and Recognition (IJDAR) 24(1), 3–17, Springer Berlin Heidelberg 2021.
• Motion Segmentation & Multiple Object Tracking by Correlation Co-Clustering, M. Keuper, S. Tang, B. Andres, T. Brox and B. Schiele, IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), vol. 42, no. 1, pp. 140–153, 1 Jan. 2020.

Selected Peer Reviewed Conference Papers

• DCBM: Data-Efficient Visual Concept Bottleneck Models, K. Prasse, P. Knab, S. Marton, C. Bartelt, M. Keuper,  International Conference on Machine Learning (ICML) 2025.
• Balancing Diversity and Risk in LLM Sampling: How to Select Your Method and Parameter for Open-Ended Text Generation, Y. Zhou, M. Keuper, M. Fritz, Annual Meeting of the Association for Computational Linguistics (ACL) 2025.
• Segment any Repeated Object, Y. Liu, C. Graf, M. Spies, M. Keuper, IEEE International Conference on Robotics and Automation (ICRA)
• VSTAR: Generative Temporal Nursing for Longer Dynamic Video Synthesis, Y. Li, W. Beluch, M. Keuper, D. Zhang, A. Khoreva, International Conference on Representation Learning (ICLR) 2025.
• Can we talk models into seeing the world differently? P. Gavrikov, J. Lukasik, S. Jung, R. Geirhos, M.J. Mirza, M. Keuper, J. Keuper, International Conference on Representation Learning (ICLR) 2025.
• I Spy With My Little Eye: A Minimum Cost Multicut Investigation of Dataset Frames , K. Prasse, I. Bravo, S. Walter, M. Keuper , Winter Conference on Computer Vision (WACV) 2025.
• Fair-TAT: Improving Model Fairness Using Targeted Adversarial Training, T. Medi, S. Jung, M. Keuper, Winter Conference on Computer Vision (WACV) 2025.
• Improving Stability during Upsampling-- Spectral Artifacts and the Importance of Spatial Context, S. Agnihotri, J. Grabinski, M. Keuper, European Conference on Computer Vision (ECCV) 2024.
• CosPGD: A unified white-box adversarial attack for pixel-wise prediction tasks, S. Agnihotri, S. Jung, M. Keuper, International Conference on Machine Learning (ICML) 2024.
• MultiMax: Sparse and Multi-Modal Attention Learning, Y. Zhou, M. Fritz, M. Keuper, International Conference on Machine Learning (ICML) 2024.
• Implicit Representations for Constrained Image Segmentation ,J. P. Schneider, M. Fatima, J. Lukasik, A. Kolb, M. Keuper, M. Moeller, International Conference on Machine Learning (ICML) 2024.
• Adversarial Supervision Makes Layout-to-Image Diffusion Models Thrive, Y. Li, M. Keuper, D. Zhang, A. Khoreva, International Conference on Representation Learning (ICLR) 2024.
• Neural Architecture Design and Robustness: A Dataset, S. Jung, J. Lukasik, M. Keuper, International Conference on Representation Learning (ICLR), 2023.
• Divide & Bind Your Attention for Improved Generative Semantic Nursing, Y. Li, M. Keuper, D. Zhang, A. Khoreva, British Machine Vision Conference (BMVC), 2023 (oral).
• Intra-Source Style Augmentation for Improved Domain Generalization, Y. Li, D. Zhang, A. Khoreva, M. Keuper, Winter Conference on Computer Vision (WACV) 2023.
• Trading-off Image Quality for Robustness is not necessary with Deterministic Autoencoders, A. Saseendran, K. Skubsch, M. Keuper, Advances in Neural Information Processing Systems (NeurIPS), 2022 (spotlight).
• Robust Models are Less Over-Confident, J. Grabinski, P. Gavrikov, J. Keuper, M. Keuper, Advances in Neural Information Processing Systems (NeurIPS), 2022.
• Learning Where to Look -- Generative NAS is Surprisingly Efficient, J. Lukasik, S. Jung, M. Keuper, European Conference on Computer Vision (ECCV), 2022.
• FrequencyLowCut Pooling -- Plug & Play against Catastrophic Overfitting, J. Grabinski, S. Jung, J. Keuper, M. Keuper, European Conference on Computer Vision (ECCV), 2022.
• Surrogate NAS Benchmarks: Going beyond the limited search space of tabular NAS benchmarks, J. Siems, L. Zimmer, A. Zela, J. Lukasik, M. Keuper and F. Hutter, International Conference on Learning Representations (ICLR), 2022.
• Learning to solve Minimum Cost Multicuts efficiently using Edge-Weighted Graph Convolutional Neural Networks, S. Jung, M. Keuper, ECML-PKDD 2022.
• Shape your Space: A Gaussian Mixture Regularization Approach to Deterministic Autoencoders, A. Saseendran, K. Skubch, S. Falkner, M. Keuper, Advances in Neural Information Processing Systems (NeurIPS), 2021.
• Multi-Class Multi-Instance Count Conditioned Adversarial Image Generation, A. Saseendran, K. Skubsch, M. Keuper, International Conference on Computer Vision (ICCV), 2021.
• Beyond the Spectrum: Detecting Deepfakes via Re-Synthesis, Y. He, N. Yu, M. Keuper and M. Fritz, International Joint Conference on Artificial Intelligence (IJCAI), 2021.
• Uncertainty in Minimum Cost Multicuts for Image and Motion Segmentation, A. Kardosst and M. Keuper, Uncertainty in Artificial Intelligence (UAI), 2021.
• Spectral Distribution Aware Image Generation, S. Jung, M. Keuper, AAAI Conference on Artificial Intelligence 2021.
• Watch your Up-Convolution: CNN Based Generative Deep Neural Networks are Failing to Reproduce Spectral Distributions, R. Durall, M. Keuper, F.J. Pfreundt, J. Keuper, Intl. Conference on Computer Vision and Pattern Recognition (CVPR) 2020.
• Occlusions, Motion and Depth Boundaries with a Generic Network for Disparity, Optical Flow or Scene Flow Estimation, E. Ilg, T. Saikia, M. Keuper, T. Brox, European Conference on Computer Vision (ECCV), 2018.
• Higher-Order Minimum Cost Lifted Multicuts for Motion Segmentation, M. Keuper, International Conference on Computer Vision (ICCV), 2017.
• Joint optical flow and uncertainty estimation, A. S. Wannenwetsch, M. Keuper, and S. Roth, International Conference on Computer Vision (ICCV), 2017.
• STD2P: RGBD Semantic Segmentation Using Spatio-Temporal Data Driven Pooling, Y. He, W.-C. Chiu, M. Keuper, M. Fritz , Conference on Computer Vision and Pattern Recognition (CVPR), 2017.
• FlowNet 2.0: Evolution of Optical Flow Estimation with Deep Networks, E. Ilg, N. Mayer, T. Saikia, M. Keuper, A. Dosovitskiy, T. Brox, Conference on Computer Vision and Pattern Recognition (CVPR), 2017.
• Motion Trajectory Segmentation via Minimum Cost Multicuts, M. Keuper, B. Andres, T. Brox, International Conference on Computer Vision (ICCV), 2015.
• Efficient Decomposition of Image and Mesh Graphs by Lifted Multicuts, M. Keuper, E. Levinkov, N. Bonneel, G. Lavoue, T. Brox, B. Andres, International Conference on Computer Vision (ICCV), 2015.
• Spectral graph reduction for efficient image and streaming video segmentation, F. Galasso, M. Keuper, T. Brox, B. Schiele, Conference on Computer Vision and Pattern Recognition (CVPR), 2014. (oral).
• Blind deconvolution of widefield fluorescence microscopic data by regularization of the optical transfer function (OTF), M. Keuper, T. Schmidt, M. Temerinac-Ott, J. Padeken, P. Heun, O. Ronneberger, T. Brox, Conference on Computer Vision and Pattern Recognition (CVPR), 2013.