Image fusion aims to integrate complementary information from diverse source images, generating a composite image with higher quality, increased information content, and enhanced clarity. Infrared and visible light image fusion (IVIF) stands out as a focal point in the field of image fusion. This paper employs the Systematic Review method to conduct a comprehensive analysis and review of the publication trends in the last two decades within three major engineering online literature databases related to IVIF. The focus is on an in-depth examination and presentation of IVIF algorithms based on deep learning till August 2023. Additionally, a systematic analysis of performance evaluation methods in the IVIF domain is provided, including a categorized comparison of various evaluation method formulas and their specific components. Finally, the paper concludes with a summary and outlook on the future technological trends in IVIF, offering valuable insights for prospective research in this field.