I am an assistant professor at the Technical University of Darmstadt, as well as a member of the Hessian Center for Artificial Intelligence (hessian.AI). The focus of my research is on developing efficient, robust, and understandable methods and algorithms for image and video analysis. I recently got the renowned Emmy Noether Programme (ENP) fund of the German Research Foundation (DFG) supporting my research on Interpretable Neural Networks for Dense Image and Video Analysis. Before starting my own group, I was a postdoctoral researcher in the Visual Inference Lab of Prof. Stefan Roth. Prior to joining TU Darmstadt, I was a postdoctoral researcher at the Media Technology Center at ETH Zurich working on augmented reality. I obtained my doctoral degree from ETH Zurich, advised by Prof. Dr. Markus Gross and in collaboration with Disney Research Zurich. In my doctoral thesis, awarded with the ETH Medal, I developed novel methods for motion representation and video frame interpolation.

News

Publications

Removing Cost Volumes from Optical Flow Estimators S. Kiefhaber, S. Roth, S. Schaub-Meyer 2025 ICCV   (Oral Presentation) 2025 GCPR Nectar Track

ART: Adaptive Relation Tuning for Generalized Relation Detection G. Sudhakaran, H. Shindo, P. Schramowski, S. Schaub-Meyer, K. Kersting, S. Roth 2025 ICCV Preprint (arXiv) | Code

Motion-refined Dinosaur for Unsupervised Multi-Object Discovery, X. Gong*, O. Hahn*, C. Reich, K. Singh, S. Schaub-Meyer, D. Cremers, S. Roth 2025 ICCV Workshop: Instance-Level Recognition and Generation (ILR)   (Oral Presentation) Preprint (arXiv) | Code

Boosting Omnidirectional Stereo Matching with a Pre-trained Depth Foundation Model J. Endres, O. Hahn, C. Corbière, S. Schaub-Meyer, S. Roth, A. Alahi 2025 IROS Preprint (arXiv) | Project page | Code

Efficient Masked Attention Transformer for Few-shot Classification and Segmentation D. Carrión-Ojeda, S. Roth, S. Schaub-Meyer 2025 GCPR 2025 ICCV Workshop: Representation Learning with Very Limited Resources: When Data, Modalities, Labels, and Computing Resources are Scarce (LIMIT) Preprint (arXiv) | Project page | Code

GLASS: Guided Latent Slot Diffusion for Object-Centric Learning K. Singh, S. Schaub-Meyer, S. Roth 2025 CVPR Preprint (arXiv) | Paper | Supplement | Talk video | Project page

Is Synthetic Data all We Need? Benchmarking the Robustness of Models Trained with Synthetic Images K. Singh, T. Navaratnam, J. Holmer, S. Schaub-Meyer, S. Roth 2024 CVPR Workshop: SyntaGen-Harnessing Generative Models for Synthetic Visual Datasets   (Best Paper Award) Preprint (arXiv) | Paper | Project page | Code

Boosting Unsupervised Semantic Segmentation with Principal Mask Proposals O. Hahn, N. Araslanov, S. Schaub-Meyer, S. Roth 2024 TMLR 2024 CVPR Workshop: Workshop on Foundation Models Preprint (arXiv) | Paper | Code

FunnyBirds: A Synthetic Vision Dataset for a Part-Based Analysis of Explainable AI Methods R. Hesse, S. Schaub-Meyer, S. Roth 2023 ICCV   (Oral Presentation) 2023 GCPR Nectar Track Paper | Supplement | Talk video | Code

Entropy-driven Unsupervised Keypoint Representation Learning in Videos A. Younes, S. Schaub-Meyer, G. Chalvatzaki 2023 ICML Paper | Project page | Code

Content-Adaptive Downsampling in Convolutional Neural Networks R. Hesse, S. Schaub-Meyer, S. Roth 2023 CVPR Workshop: Efficient Deep Learning for Computer Vision Paper | Supplement | Talk video | Poster | Code

Efficient Feature Extraction for High-resolution Video Frame Interpolation M. Nottebaum, S. Roth, S. Schaub-Meyer 2022 BMVC Paper | Supplement | Video | Talk video | Poster | Code

$S^2$-Flow: Joint Semantic and Style Editing of Facial Images K. Singh, S. Schaub-Meyer, S. Roth 2022 BMVC Paper | Supplement | Talk video | Poster | Code

Fast Axiomatic Attribution for Neural Networks R. Hesse, S. Schaub-Meyer, S. Roth 2021 NeurIPS Paper | Supplement | Talk video | Project page | Code

Dense Unsupervised Learning for Video Segmentation N. Araslanov, S. Schaub-Meyer, S. Roth 2021 NeurIPS Paper | Supplement | Video | Talk video | Code

Style Transfer for Keypoint Matching Under Adverse Conditions A. Uzpak, A. Djelouah, S. Schaub-Meyer 2020 3DV Paper | Code

Neural inter-frame compression for video coding A. Djelouah, J. Campos, S. Schaub-Meyer, C. Schroers 2019 ICCV Paper | Supplement

Deep Video Color Propagation S. Meyer, V. Cornillère, A. Djelouah, C. Schroers, M. Gross 2018 BMVC Preprint (arXiv) | Paper | Supplement | Video

PhaseNet for Video Frame Interpolation S. Meyer, A. Djelouah, B. McWilliams, A. Sorkine-Hornung, M. Gross, C. Schroers 2018 CVPR Paper | Supplement | Video | BibTex

Phase-Based Modification Transfer for Video S. Meyer, A. Sorkine-Hornung, M. Gross 2016 ECCV   (Oral Presentation) Paper | Video

Phase-based Frame Interpolation for Video S. Meyer, O. Wang, H. Zimmer, M. Grosse, A. Sorkine-Hornung 2015 CVPR   (Oral Presentation) Paper | Supplement | Video | Code