Aiming at the problem of low detection accuracy of occluded pedestrian in traffic environments,this paper proposes a key points and visible part fusion network for ocluded pedestrian detection.The proposed algorithm constructs two attention modules by introducing human key points and the bounding box of visible parts respectively,which suppresses the oc- cluded parts in the channel features and spatial features of pedestrian features respectively.Experimental results on CityPersons and Caltech datasets demonstrate the effectiveness of the proposed algorithm.The missing rate(MR)is re- duced to 40.78 on the Heavy subset of the CityPersons dataset and surpasses many outstanding methods.