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Author

Joachim Sicking

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2 papers indexed here

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Preprint Sep 2026

Diffuse2Seg: Diffusion Models Can Segment Anything Without Supervision

Diffuse2Seg is introduced, which repurposes generative diffusion models for automatic mask generation by propagating a grid of point prompts through their self-attention representations in an edge-preserving manner, and shows that a model trained on Diffuse2Seg labels provides a strong initialization for semi-supervise...

Christoph Hümmer, Joachim Sicking, Fabian Hüger et al. · 0 citations
Preprint Aug 2026

RoG-DAgger: Rollout-Guided Post-Training for End-to-End Driving

RoG-DAgger is introduced, a post-training framework that uses short-horizon kinematic rollouts to construct high-quality expert demonstrations in safety-critical states and aligns the expert's field of view with that of the student to provide student-compatible supervision.

Liangyu Zhong, Joachim Sicking, Fabian Hueger et al. · 0 citations

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