Aiming at the problems of low detection accuracy for objects with non-significant features in the FCOS network, a new object detection method based on attention mechanism is proposed to improve the performance of FCOS network, which can effectively guide the network to focus on the detailed features. According to the verification experimental results on KITTI dataset, the AP value of the improved attention mechanism-based method for car and person detection is improved by 1.1% and 4.9% compared with the standard FCOS network, respectively, and the average category accuracy value is improved by 3%. Thus, the experimental results show the effectiveness of the proposed method.