38 citations · 94 across the 18 of their papers we have counts for
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cs.CV2026
Combining Foundation Model Confidence and Monocular Depth for Training-Free Out-of-Distribution Segmentation
Serin Varghese, Fabian Hüger, Kira Maag
Autonomous vehicles operating in open-world scenarios are inevitably confronted with previously unknown objects, such as exotic animals or loose cargo. The reliable detection and s…
cs.CV2026
Diffuse2Seg: Diffusion Models Can Segment Anything Without Supervision
Christoph Hümmer, Joachim Sicking, Fabian Hüger +1
Open-world entity segmentation aims to predict masks for arbitrary objects across domains and at multiple granularities, from parts to whole objects. In this setting, SAM sets a st…
cs.CV2026
Do Not Forget the Obvious - RISC: A Risk-Informed Slice-Coverage Protocol for Safe Autonomous Driving
Fabian Hüger
Aggregate metrics may not fully reflect performance in insufficiently examined high-risk driving conditions. We propose RISC (Risk-Informed Slice Coverage), a practical protocol fo…