EVIAC

The EVIAC dataset is a large-scale enhanced benchmark for visible\u2013infrared camouflaged object detection, built upon our previous VIAC dataset of 1,500 visible\u2013infrared pairs captured via a dual-spectrum UAV system. To enhance diversity, a style transfer algorithm is applied to generate three additional environments\u2014forest, fog, and snow\u2014yielding 6,000 precisely aligned visible\u2013infrared pairs across four scenes. EVIAC maintains structural and semantic consistency during style transfer, ensuring automatic ground-truth inheritance without extra labeling. It provides rich variability in illumination, object scale, and distribution, and includes annotations for 9 challenge factors (BCO, SCO, MCO, CB, OV, OC, TC, IC, LI). This makes EVIAC a diverse, reliable, and cost-efficient benchmark for studying multimodal perception under complex camouflage conditions.