Prof.

Stefan Roth, PhD

Technische Universität Darmstadt Visual Inference
Hochschulstraße 10
64289 Darmstadt

+49 (0)6151 16 21 425 +49 (0)6151 16 25 412 Send e-mail Visit website

Short info

My research focuses on machine learning approaches to understanding and analyzing digital images and videos. My lab and I develop new deep learning models and methods for scene understanding, motion estimation, image editing and synthesis, video analysis, image restoration, and more. We aim to make such approaches robust to a broad range of real-world conditions. To that end, we are incorporating inductive biases through combining deep learning with classical models, endowing deep networks with explicit representations of uncertainty, or adapting pre-trained models to changing test-time circumstances. We also aim to reduce the dependency on labeled data by developing semi-supervised and self-supervised learning pipelines.

Open Science
Hahn, O., Araslanov, N., Schaub-Meyer, S., & Roth, S. (2024).
Boosting Unsupervised Semantic Segmentation with Principal Mask Proposals.
arXiv preprint2404.16818.
DOI
Articles
Bahmani, S., Hahn, O., Zamfir, E., Araslanov, N., Cremers, D., & Roth, S. (2022).
Semantic Self-adaptation: Enhancing Generalization with a Single Sample. Transactions on Machine Learning Research (TMLR).
DOI
Hesse, R., Schaub-Meyer, S., & Roth, S. (2021).
Fast axiomatic attribution for neural networks.
Advances in Neural Information Processing Systems, 34(2), 19513-19524.
DOI