Target detection technology based on infrared detection systems has been widely used in security, early warning, and other fields. However, due to the weak signal and small feature scale of infrared dim and small targets, problems such as missed detection, false detection, and false alarms are prone to occur in complex application scenarios. Significant progress has been made in infrared dim and small target detection based on traditional image processing methods and deep learning algorithms. This paper discusses the latest research progress in infrared dim and small target detection methods, covering single-frame detection methods, multi-frame detection methods, and deep learning methods. It analyzes the advantages and limitations of existing technologies and summarizes the future development direction of infrared dim and small target detection algorithms.