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The detection of seatbelt wearing behavior of vehicle-borne personnel plays an important role in ensuring human life safety. Aiming at the problem of low detection accuracy of seat belt worn by vehicle occupants in complex environment, an improved detection method based on YOLOv5s(You Only Look Once v5s) was proposed. The detection method takes YOLOv5s as the basic network and improves on it. In order to improve the ability of the depth model to extract feature information, the Receptive Field of the network is expanded by using the receptive field RFB(Receptive Field Block) module, and the hybrid receptive field is obtained by using the multi-branch structure of the RFB module. Adding the Efficient Channel Attention ECA(Efficient Channel Attention) module makes the entire network focus more on extracting feature information. The loss function of the original YOLOv5s is replaced by EIOU to further improve the detection accuracy of the safety belt. The experimental results show that compared with the original YOLOv5s network, the mAP (mean Average Precision) of the improved network is increased by 2.2%, and the Precision is increased by 5.1%. The improved network has good enhancement effect, which shows the effectiveness of the method.