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RGB-to-IR image translation for infrared vehicle detection in unseen UAV domains
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 motivates RGB-to-IR translation for data augmentation, unobservable thermal traits (e.g., engine heat) make learning transferable mappings challenging. This work investigates whether modern generative translators can overcome this cross-modal gap to improve infrared vehicle detection on unseen UAV target domains. Translators are trained on paired RGB-IR source datasets and applied to RGB training images from held-out ta
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Evidence & attribution
- arXiv · AI, language, vision and robotics · 2026-09-02T13:06:58.000Z
First collected: 2026-09-21T05:32:15.665Z. This is not the publication date.