Heart rate and saturation of peripheral capillary oxygenation (SpO₂) are very important physiological indicators of human health. In recent years, non-contact heart rate and SpO₂ detection methods based on imaging photoplethysmography (IPPG) have gradually become a research focus as they are convenient and freely-applied. The main work is as follows. First, the study introduces the background and research significance of non-contact detection methods. Secondly, two aspects of target region detection and region of interest (ROI) are selected to summarize and clarify the research status and future improvement direction. Thirdly, the detection methods of heart rate and SpO₂ are summarized from three aspects: traditional method, signal processing combined with deep learning method and end-to-end method, and the data sets used in deep learning method and the detection effects displayed in each data set are sorted out. Finally, the paper points out the problems that need to be solved and the future research direction in this field.