activity
20242026
collaborators

9 papers

cs.CV2026

Show Me Examples: Inferring Visual Concepts from Image Sets

Nick Stracke, Kolja Bauer, Stefan Andreas Baumann +3

Vision-language models (VLMs) can follow complex textual instructions, yet they struggle to reason from purely visual context. In particular, current models fail to infer shared co…

cs.CV2026

RayDer: Scalable Self-Supervised Novel View Synthesis from Real-World Video

Ulrich Prestel, Stefan Andreas Baumann, Nick Stracke +1

Self-supervised novel view synthesis (NVS) remains challenging to scale, despite the abundance of video data, largely due to the brittleness of training on realistic videos and the…

cs.CV2026

Probabilistic Precipitation Nowcasting with Rectified Flow Transformers

Johannes Schusterbauer, Jannik Wiese, Nick Stracke +2

Accurate weather forecasts are essential across various domains and are safety-critical in extreme weather conditions. Compared to simulation-based forecasting, data-driven approac…

cs.CV2026

Learning Long-term Motion Embeddings for Efficient Kinematics Generation

Nick Stracke, Kolja Bauer, Stefan Andreas Baumann +3

Understanding and predicting motion is a fundamental component of visual intelligence. Although modern video models exhibit strong comprehension of scene dynamics, exploring multip…

cs.CV2025

CleanDIFT: Diffusion Features without Noise

Nick Stracke, Stefan Andreas Baumann, Kolja Bauer +2

Internal features from large-scale pre-trained diffusion models have recently been established as powerful semantic descriptors for a wide range of downstream tasks. Works that use…

cs.CV2025

What If : Understanding Motion Through Sparse Interactions

Stefan Andreas Baumann, Nick Stracke, Timy Phan +1

Understanding the dynamics of a physical scene involves reasoning about the diverse ways it can potentially change, especially as a result of local interactions. We present the Flo…