Abstract: Rice diseases and pests have a serious impact on rice growth and yield．Therefore, it is crucial to effectively identify and intervene in initial stages of diseases and pests to ensure rice growth．Object detection technology of rice diseases and pests can achieve relatively accurate automated identification．With rapid development of deep learning in recent years, object detection technology has also made important progress, such as YOLO algorithm, Faster R-CNN algorithm, etc．Development and research progress of rice diseases and pests object detection technology were introduced, improved algorithms and highlights proposed by scholars in recent years were analyzed, application scenarios and shortcomings of different types of algorithms in the field of rice diseases and pests object detection were discussed, and future development and research direction were explored, in order to promote object detection technology to assist rice planting research．