Obtaining high-precision, high-resolution precipitation data is of great significance for hydrological analysis, water resources management, and flood and drought monitoring. Although remote-sensing precipitation products can effectively reproduce the spatial and temporal distribution of precipitation, few original remote-sensing precipitation products can meet the requirements in either precision or resolution in the hydrological field. It is therefore necessary to carry out post-processing research on existing remote-sensing precipitation products. The main methods used to obtain precipitation data are introduced, including rain-gauge observations, weather radar estimates, and satellite products. The advantages of each method and their problems are discussed. Next, the research advances made in post-processing methods of remote-sensing precipitation products are summarized, including spatial downscaling, bias correction, and multi-product fusion. Then, the indices used for evaluation of post-processing precipitation products are reviewed. Finally, the following research directions that must be pursued more avidly in the future are discussed: development and improvement of precipitation-estimation techniques, construction of a more reasonable framework for multi-source precipitation data fusion, strengthening of the comparative study of downscaling methods and ideas for their improvement, and uncertainty analysis.