Transmission line small object detection based on Gromov-Wassertein optimal transport
In order to address the issue of severe performance degradation of target detection algorithms in the scenario of unmanned aerial vehicle(UAV)line inspection for power transmission lines,specifically when dealing with small targets such as line defects and missing components,a new loss function was proposed from the perspective of label assignment to improve the accuracy and ef-fectiveness of small target detection.Different from traditional target detection methods,each predicted bounding box was treated as a Gaussian receptive field,and the ground truth value was treated as a Gaussian heat map.Label assignment was performed by calcu-lating the distance between two Gaussian distributions.A Gromov-Wassertein optimal transport-guided model learning method was introduced,which could be built upon existing detection models.Experimental results on multiple power transmission line target de-tection datasets demonstrated that the label assignment scheme using Gaussian receptive fields and optimal transport had achieved good performance in small target detection during power transmission line inspection.
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