Images captured under low-light conditions are often characterized by low brightness and contrast, color distortion, and high noise, which seriously affect the subjective vision of human eyes and greatly limit the performance of higher-order vision tasks. Low illuminance image enhancement (LIIE) aims to improve the visual effect of such images and provide favorable conditions for subsequent processing. Among many low-illuminance image enhancement algorithms, the LIIE based on deep learning has become the latest solution. Firstly, the representative methods for LIIE based on deep learning were reviewed. Secondly, the existing low-illuminance image datasets, loss functions, and evaluation indicators were introduced. Thirdly, the existing LIIE algorithms based on deep learning were comprehensively evaluated through benchmark testing and experimental analysis. Finally, a summary of current research was provided, and the development direction of LIIE was discussed and prospected.