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2023
- S. Jung, J. Lukasik, M. Keuper, Neural Architecture Design and Robustness: A Dataset, accepted to ICLR 2023
- Y. Li, D. Zhang, M. Keuper, A. Khoreva, Intra-Source Style Augmentation for Improved Domain Generalization, WACV 2023.
2022
- P. Mueller, A. Braun and M. Keuper, Impact of realistic properties of the point spread function on classification tasks to reveal a possible distribution shift, NeurIPS 2022 Workshop on Distribution Shifts: Connecting Methods and Applications, 2022.
- Y. Zhou, W., Xiang, C. Li, B. Wang, X. Wei, L. Zhang, M. Keuper, X., Hua, SP-VIT: Learning 2D Spatial Priors for Vision Transformers, BMVC 2022.
- J. Grabinski, P. Gavrikov, J. Keuper, M. Keuper, Robust Models are Less Over-Confident, NeurIPS 2022.
- A. Saseendran, K. Skubsch, S. Falkner, M. Keuper, Trading-off Image Quality for Robustness is not necessary with Regularized Deterministic Autoencoders, NeurIPS 2022.
- J. Lukasik, S. Jung, M. Keuper, Learning Where to Look -- Generative NAS is Surprisingly Efficient, ECCV 2022.
- J. Grabinski, S. Jung, J. Keuper, M. Keuper, FrequencyLowCut Pooling -- Plug & Play against Catastrophic Overfitting, ECCV 2022.
- J. Grabinski, J. Keuper, M. Keuper, Aliasing and adversarial robust generalizaiton of CNNs, Machine Learning, 2022.
- S. Jung, M. Keuper, Learning to solve Minimum Cost Multicuts efficiently using Edge-Weighted Graph Convolutional Neural Networks, ECML-PKDD 2022.
- S. Jung, S. Ziegler, A. Kardoost, M. Keuper, Optimizing Edge Detection for Image Segmentation with Multicut Penalties, GCPR 2022.
- E. Levinkov*, A. Kardoost*, B. Andres and M. Keuper (*equal contribution), "Higher-Order Multicuts for Geometric Model Fitting and Motion Segmentation," in IEEE Transactions on Pattern Analysis and Machine Intelligence, doi: 10.1109/TPAMI.2022.3148795.
- J. Siems, L. Zimmer, A. Zela, J. Lukasik, M. Keuper and F. Hutter, NAS-Bench-301 and the Case for Surrogate Benchmarks for Neural Architecture Search, ICLR, 2022.
- P Lorenz, D Strassel, M Keuper, J Keuper, Is RobustBench/AutoAttack a suitable Benchmark for Adversarial Robustness? The AAAI-22 Workshop on Adversarial Machine Learning and Beyond, 2022.
- J Grabinski, J Keuper, M Keuper, Aliasing coincides with CNNs vulnerability towards adversarial attacks The AAAI-22 Workshop on Adversarial Machine Learning and Beyond, 2022.
- K. Ho, FJ Pfreundt, J Keuper, M Keuper, Estimating the Robustness of Classification Models by the Structure of the Learned Feature-Space, The AAAI-22 Workshop on Adversarial Machine Learning and Beyond, 2022.
2021
- A. Saseendran, K. Skubch, S. Falkner, M. Keuper, Shape your Space: A Gaussian Mixture Regularization Approach to Deterministic Autoencoders: , NeurIPS 2021.
- S Jung, M Keuper, Internalized Biases in Fréchet Inception Distance, NeurIPS 2021 Workshop on Distribution Shifts, 2021.
- J Geiping, J Lukasik, M Keuper, M Moeller, DARTS for Inverse Problems: a Study on Sensitivity, NeurIPS workshop on Inverse Problems, 2021.
- J Geiping, J Lukasik, M Keuper, M Moeller, DARTS for Inverse Problems: a Study on Hyperparameter Sensitivity, arXiv preprint arXiv:2108.05647
- P Lorenz, P Harder, D Straßel, M Keuper, J Keuper, Detecting AutoAttack Perturbations in the Frequency Domain, ICML 2021 Workshop on Adversarial Machine Learning
- S Jung, M Keuper, Spectral Distribution aware Image Generation, arXiv preprint arXiv:2012.03110, accepted at AAAI 2021
- K. Ho, F.-J. Pfreundt, J Keuper, M Keuper, Estimating the Robustness of Classification Models by the Structure of the Learned Feature-Space, https://arxiv.org/abs/2106.12303 (link is external)
- Y He, N Yu, M Keuper, M Fritz, Beyond the Spectrum: Detecting Deepfakes by Image Re-Synthesis, IJCAI 2021.
- A Kardoost, M Keuper, Uncertainty in Minimum Cost Multicuts for Image and Motion Segmentation, arXiv preprint arXiv:2105.07469, UAI 2021.
- A Saseendran, K Skubch, M Keuper, Multi-Cluass Multi-Instance Count Conditioned Adversarial Image Generation, arXiv preprint arXiv:2103.16795, ICCV 2021.
- P Harder, FJ Pfreundt, M Keuper, J Keuper, SpectralDefense: Detecting Adversarial Attacks on CNNs in the Fourier Domain, arXiv preprint arXiv:2103.03000, IJCNN 2021.
- J Lukasik, D Friede, A Zela, F Hutter, M Keuper, Smooth variational graph embeddings for efficient neural architecture search, arXiv preprint arXiv:2010.04683, IJCNN 2021.
- K Ho, A Chatzimichailidis, M Keuper, J Keuper, MSM: Multi-stage Multicuts for Scalable Image Clustering, International Conference on High Performance Computing, 267-284, 2021.
- Schäfer, B., Keuper, M. und Stuckenschmidt, H. (2021). Arrow R-CNN for handwritten diagram recognition. International Journal on Document Analysis and Recognition : IJDAR, 24, 3-17.
2020
- J Lukasik, M Keuper, M Singh, J Yarkony, A Benders Decomposition Approach to Correlation Clustering, 2020 IEEE/ACM Workshop on Machine Learning in High Performance Computing at SC20
- J Lukasik, D Friede, H Stuckenschmidt, M Keuper, Neural Architecture Performance Prediction Using Graph Neural Networks, DAGM German Conference on Pattern Recognition, 188-201
- J Siems, L Zimmer, A Zela, J Lukasik, M Keuper, F Hutter, NAS-Bench-301 and the case for surrogate benchmarks for neural architecture search, arXiv preprint arXiv:2008.09777
- R Durall, M Keuper, J Keuper, Watch your up-convolution: Cnn based generative deep neural networks are failing to reproduce spectral distributions, Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2020.
- K Ho, J Keuper, M Keuper, Unsupervised multiple person tracking using autoencoder-based lifted multicuts, arXiv preprint arXiv:2002.01192
- K Ho, A Kardoost, FJ Pfreundt, J Keuper, M Keuper, A two-stage minimum cost multicut approach to self-supervised multiple person tracking, Proceedings of the Asian Conference on Computer Vision,2020.
- A Kardoost, K Ho, P Ochs, M Keuper, Self-supervised sparse to dense motion segmentation, Proceedings of the Asian Conference on Computer Vision, 2020.
- K Ho, J Keuper, FJ Pfreundt, M Keuper, Learning embeddings for image clustering: An empirical study of triplet loss approaches, 2020 25th International Conference on Pattern Recognition (ICPR), 87–94
- A Kardoost, S Müller, J Weickert, M Keuper, Object Segmentation Tracking from Generic Video Cues, 2020 25th International Conference on Pattern Recognition (ICPR), 623–630
- Primpeli, A., Bizer, C. und Keuper, M. (2020). Unsupervised bootstrapping of active learning for entity resolution. In , The Semantic Web : 17th International Conference, ESWC 2020, Heraklion, Crete, Greece, May 31-June 4, 2020, Proceedings (S. 215-231). Lecture Notes in Computer Science, Springer International Publishing: Cham.
- Keuper, M., Tang, S., Andres, B., Brox, T. und Schiele, B. (2020). Motion segmentation & multiple object tracking by correlation co-clustering. IEEE Transactions on Pattern Analysis and Machine Intelligence, 42, 140-153.
2019
- Kardoost, A. und Keuper, M. (2019). Solving minimum cost lifted multicut problems by node agglomeration. In , Computer Vision – ACCV 2018 : 14th Asian Conference on Computer Vision, Perth, Australia, December 2–6, 2018, Revised Selected Papers, Part IV (S. 74-89). Lecture Notes in Computer Science, Springer: Cham.
2018
- Broscheit, S., Gemulla, R. und Keuper, M. (2018). Learning distributional token representations from visual features. In , ACL 2018, Representation Learning for NLP : Proceedings of the Third Workshop : July 20, 2018 Melbourne, Australia (S. 187-194). , Association for Computational Linguistics: Stroudsburg, PA.
- Ilg, E., Saikia, T., Keuper, M. und Brox, T. (2018). Occlusions, motion and depth boundaries with a generic network for disparity, optical flow or scene flow estimation. In , Computer Vision – ECCV 2018 : 15th European Conference, Munich, Germany, September 8–14, 2018, Proceedings, Part XII (S. 626-643). Lecture Notes in Computer Science, Springer: Cham.
- Gemulla, R., Ponzetto, S. P., Bizer, C., Keuper, M. und Stuckenschmidt, H. (eds.) (2018). LWDA 2018 : Proceedings of the Conference „Lernen, Wissen, Daten, Analysen“, Mannheim, Germany, August 22-24, 2018.
2017
- He, Y., Chiu, W.-C., Keuper, M. und Fritz, M. (2017). STD2P: RGBD semantic segmentation using spatio-temporal data-driven pooling. In , 30th IEEE Conference on Computer Vision and Pattern Recognition : CVPR 2017 : 21–26 July 2016, Honolulu, Hawaii : proceedings (S. 7158-7167). , IEEE: Piscataway, NJ.
- He, Y., Keuper, M., Schiele, B. und Fritz, M. (2017). Learning dilation factors for semantic segmentation of street scenes. In , Pattern Recognition : 39th German Conference, GCPR 2017, Basel, Switzerland, September 12–15, 2017, Proceedings (S. 41-51). Lecture Notes in Computer Science, Springer: Cham.
- Ilg, E., Mayer, N., Saikia, T., Keuper, M., Dosovitskiy, A. und Brox, T. (2017). FlowNet 2.0: Evolution of optical flow estimation with deep networks. In , 30th IEEE Conference on Computer Vision and Pattern Recognition : CVPR 2017 : 21–26 July 2016, Honolulu, Hawaii : proceedings (S. 1647-1655). , IEEE: Piscataway, NJ.
- Keuper, M. (2017). Higher-order minimum cost lifted multicuts for motion segmentation. In , 2017 IEEE International Conference on Computer Vision : ICCV 2017 : proceedings : 22 – 29 October 2017, Venice, Italy (S. 4252 -4260). , IEEE: Piscataway, NJ.
- Wannenwetsch, A. S., Keuper, M. und Roth, S. (2017). ProbFlow: Joint optical flow and uncertainty estimation. In , 2017 IEEE International Conference on Computer Vision : ICCV 2017 : proceedings : 22 – 29 October 2017, Venice, Italy (S. 1182-1191). , IEEE: Piscataway, NJ.
2016
- Keuper, M. und Brox, T. (2016). Point-wise mutual information-based video segmentation with high temporal consistency. In , Computer Vision – ECCV 2016 Workshops : Amsterdam, The Netherlands, October 8–10 and 15-16, 2016, Proceedings, Part III (S. 789-803). Lecture Notes in Computer Science, Springer: Berlin.