3 papers
cs.CV2026
Domain generalization and synthetic data in object detection: the enabler, the probe, and the gap
Elfi I. S. Hofmeijer, Ella P. Fokkinga, Friso G. Heslinga +2
Object detection models often experience performance degradation when deployed under distribution shifts, caused by for example changes in weather type, operational environment, or…
cs.CV2026
RGB-to-IR image translation for infrared vehicle detection in unseen UAV domains
Thijs A. Eker, Ella P. Fokkinga, Jan Erik van Woerden +4
Synthetic training data is crucial for developing vision AI when real-world data is scarce, as in thermal infrared (IR) aerial vehicle detection. While abundant UAV RGB imagery mot…
cs.CV2026
Class-specific diffusion models improve military object detection in a low-data domain
Ella P. Fokkinga, Jan Erik van Woerden, Thijs A. Eker +4
Diffusion-based image synthesis has emerged as a promising source of synthetic training data for AI-based object detection and classification. In this work, we investigate whether…