YOLO-ROC reports 67.6% mAP50 on RDD2022_China_Drone with 0.89M parameters, a 1.4-point gain over YOLOv8n.
In: Proceedings of the IEEE Conference on Computer Vi- sion and Pattern Recognition (CVPR), pp
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YOLO-ROC: A High-Precision and Ultra-Lightweight Model for Real-Time Road Damage Detection
YOLO-ROC reports 67.6% mAP50 on RDD2022_China_Drone with 0.89M parameters, a 1.4-point gain over YOLOv8n.