For high-voltage transmission lines, there will be foreign bodies affecting the normal operation of the line. This paper proposes an improved CenterNet method for detecting foreign bodies in high-voltage transmission line inspection to detect common small targets of foreign bodies in transmission lines. In this method, a wide residual module was designed based on cavity convolution, and the feature extraction surface of the residual module was widened. The channel attention mechanism and spatial attention mechanism were used to process the feature information twice, and the detection accuracy was optimized. The experimental results show that the improved average accuracy is improved from 88.59% to 93.09%, and the overall accuracy is improved by 4.5 percentage points.