False positives cannot be avoided in modern state-of-the-art object detectors. Non-maximum suppression (NMS) is essential as a post-processing step to eliminate the false positives caused by redundant detections for a single object. However, NMS cannot eliminate all the redundant detections which have different classification results. In order to address this problem, this paper proposes a novel post-processing step, non-reliability suppression (NRS). On PASCAL VOC, the proposed NRS reduces 28.4% false positives with only a 0.3% decrease of true positives for a YOLOv3 detector when compared with the traditional greedy-NMS. Since the computation of NRS is simple, additional complexity is minimal.