Fisheye detectionIntermediate
FUSEye: Training-Light Fisheye Detection with Overlapping Views and Zero-Initialized Adapters
This preprint introduces FUSEye, a training-light method that adapts a frozen COCO-pretrained YOLO26-x detector to fisheye camera images using overlapping views, zero-initialized residual adapters, and learned cross-view fusion. On WoodScape, it lifts mAP50 from 14.80 to 26.61, reaching 84.3% of full fine-tuning accuracy while training only about 227k added parameters. This matters because it lets robots adapt off-the-shelf detectors to wide-angle cameras without expensive full retraining or calibration.