In response to key challenges including the complexity of marine environments, the unique optical properties of water bodies, difficulties in data collection, and the lack of structured information in monocular optical images, this paper summarizes and analyzes recent significant advancements in equipment and theoretical methods related to 3D reconstruction of underwater monocular optical images. It dissects the existing issues in 3D reconstruction from three aspects: the need for enhanced maturity of monocular optical devices, insufficient research on the physical properties of underwater monocular optics, and the need for improved edge precision in reconstruction results. Addressing these key issues, we developed an underwater optical range-gated camera device and further studied a monocular optical image 3D reconstruction algorithm based on deep learning. This paper proposes potential key technologies for future 3D reconstruction of underwater scenes using monocular optical images.