3 papers
cs.CV2025
Simplifying Traffic Anomaly Detection with Video Foundation Models
Svetlana Orlova, Tommie Kerssies, Brunó B. Englert +1
Recent methods for ego-centric Traffic Anomaly Detection (TAD) often rely on complex multi-stage or multi-representation fusion architectures, yet it remains unclear whether such c…
cs.CV2025
What is the Added Value of UDA in the VFM Era?
Brunó B. Englert, Tommie Kerssies, Gijs Dubbelman
Unsupervised Domain Adaptation (UDA) can improve a perception model's generalization to an unlabeled target domain starting from a labeled source domain. UDA using Vision Foundatio…
cs.CV2025
VFM-UDA++: Improving Network Architectures and Data Strategies for Unsupervised Domain Adaptive Semantic Segmentation
Brunó B. Englert, Gijs Dubbelman
Unsupervised Domain Adaptation (UDA) enables strong generalization from a labeled source domain to an unlabeled target domain, often with limited data. In parallel, Vision Foundati…