Class-specific diffusion models fine-tuned on 8-24 real images per class generate synthetic data that improves military vehicle detection by up to 8% mAP50 in low-data regimes, with further gains from ControlNet edge conditioning.
3DSM- COS: A 3D model-based synthetic data pipeline for military camouflaged object segmentation with distractor-augmented realism
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Class-specific diffusion models improve military object detection in a low-data domain
Class-specific diffusion models fine-tuned on 8-24 real images per class generate synthetic data that improves military vehicle detection by up to 8% mAP50 in low-data regimes, with further gains from ControlNet edge conditioning.