In this paper, we propose weighted-mean YOLO to improve real-time performance of object detection by fusing information of RGB camera and LIDAR. RGB camera is vulnerable to external environments and therefore strongly affected by illumination. Conversely, LIDAR is robust to external environments, but has low resolution. Since each sensor can complement their disadvantages, we propose a method to improve the performance of object detection through sensor fusion. We design the system using weighted-mean to construct a robust system and compared with other algorithms, it shows performance improvement of missed-detection.