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This research investigates repurposing the backbone from YOLO26's depth estimation model for image deraining, demonstrating that depth-trained initialization provides a consistent improvement over random initialization in controlled experiments.
YOLO26 is a multi-task computer vision model family released in January 2026, featuring end-to-end detection without Non-Maximum Suppression for lower latency and optimized for edge deployment with improved CPU inference and compact design.