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Osnabrück Vision AI (OSVIA) Lab

The OSVIA Lab researches methods that teach machines to see – from the basics of classical computer vision to modern deep learning approaches. Our goal is to develop algorithms that process visual data reliably, efficiently, and explainably. We work on problems ranging from the recognition and analysis of complex scenes to 3D reconstruction and robust machine learning. With our research, we bridge the gap between theory and application – for advances in science, industry, and society.

Universität Osnabrück: AG Computer Vision and Robust AI

Bergische Universität Wuppertal: AG Applied and Computational Mathematics

Recent Publications

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Probabilistic Label Spreading: Efficient and Consistent Estimation of Soft Labels with Epistemic Uncertainty on Graphs

Klees , J., Riedlinger, T., Stehr, P., Böddecker, B., Kondermann, D., Rottmann, M. (2026)

Paper Project Page
Can We Challenge Open-Vocabulary Object Detectors with Generated Content in Street Scenes?

Mütze, A., Ilyas, S., Dörpelkus, C, Rottmann, A. (2025)

Paper Project Page
Temporal Object Captioning for Street Scene Videos from LiDAR Tracks

Vignesh , G., Urs, Z., Michael, A., Rottmann, M. (2025)

Paper Project Page

Datasets

Benchmark for Label Error Detection Methods in Object Detection

A Modular Framework and Benchmark for Object Detection Datasets. (2025)

Website
OoDIS

Anomaly Instance Segmentation Benchmark. (2024)

Website Project Page
SegmentMeIfYouCan

A Benchmark for Anomaly Segmentation. (2021)

Website

Projects

Ongoing and recent work with our research and industry partners.

Team

A multidisciplinary group committed to understanding and improving AI robustness in real-world scenarios.

Meet the Team

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News

Best Student Paper Award at VISAPP 2026

Best Student Paper Award at VISAPP 2026

Apr 17, 2026 Paper VISAPP 2026

Our doctoral student Martha Teiko T. received the Best Student Paper Award at VISAPP 2026 for the paper “FutrTrack A Camera-LiDAR Fusion Transformer for 3D Multiple Object Tracking,” co-authored by Ori Maoz.

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Project LiDiMoVer

Project LiDiMoVer

Mar 23, 2026 BUW EFRE-NRW

LiDiMoVer is an innovative smart city research initiative focused on advancing urban mobility.

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Paper accepted at CVPR 2026

Paper accepted at CVPR 2026

Mar 10, 2026 Paper CVPR 2026

Our paper PRIMU Uncertainty Estimation for Novel Views in Gaussian Splatting from Primitive-Based Representations of Error and Coverage” has been accepted for publication at CVPR 2026.

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Inaugural lecture by Prof. Rottmann and Prof. Mossakowski

Inaugural lecture by Prof. Rottmann and Prof. Mossakowski

Jan 20, 2026 UOS

On 20.01.2026, the Institute of Computer Science celebrated "50 years of computer science at Osnabrück University". Prior to this, Prof. Rottmann and Prof. Mossakowski presented their research areas in their inaugural lectures.

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Paper accepted at WACV 2026

Paper accepted at WACV 2026

Dec 20, 2025 Paper WACV 2026

Our paper “Can We Challenge Open-Vocabulary Object Detectors with Generated Content in Street Scenes?” has been accepted to WACV 2026.

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Workshop on Uncertainty Quantification at ControlExpert

Workshop on Uncertainty Quantification at ControlExpert

Dec 12, 2025 Workshop

The OSVIA lab joined a scientific workshop hosted at ControlExpert together with the research team of Prof. Kira Maag from Heinrich Heine University Düsseldorf and colleagues from ControlExpert.

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