2 papers
cs.CV2025
On the Domain Robustness of Contrastive Vision-Language Models
Mario Koddenbrock, Rudolf Hoffmann, David Brodmann +1
In real-world vision-language applications, practitioners increasingly rely on large, pretrained foundation models rather than custom-built solutions, despite limited transparency…
cs.CV2025
RADLER: Radar Object Detection Leveraging Semantic 3D City Models and Self-Supervised Radar-Image Learning
Yuan Luo, Rudolf Hoffmann, Yan Xia +4
Semantic 3D city models are worldwide easy-accessible, providing accurate, object-oriented, and semantic-rich 3D priors. To date, their potential to mitigate the noise impact on ra…