DPLR-DETR: Small Object Detection Model for UAV Aerial Imagery

Small object detection in UAV aerial imagery presents significant challenges due to limited pixel coverage and complex backgrounds. This paper introduces DPLR-DETR (Dynamic Position Large Receptive Field DETR), a novel architecture that enhances the RT-DETR framework to improve detection accuracy and computational efficiency in UAV applications. DPLR-DETR incorporates three key innovations: (1) an Enhanced Shifted Residual Block (ESRB) backbone for efficient feature extraction, (2) a Gated Channel Attention Multiscale Fusion module that implemented a “deep processing for small targets—lightweight preservation for backgrounds” strategy, and (3) a Dynamic Position Bias Attention (DPBA) module that enhances spatial modeling capabilities. Experimental results on the VisDrone2019 dataset demonstrate that DPLR-DETR significantly improves small object detection performance while maintaining computational efficiency suitable for resource-constrained scenarios.