In recent years, deep learning (DL) has been widely used in computational imaging (CI) and has achieved remarkable results; as such, DL has become a research hotspot in this field. To gain an in-depth understanding of how DL-based CI works, this manuscript mainly introduces the basic theory and implementation steps of DL as well as its applications in scattering imaging, digital holography, and computational ghost imaging to demonstrate its effectiveness and superiority. Some typical applications of DL in CI are summarized and compared herein, and the CI methods based on deep learning are prospected.