Multimode fibers demonstrate significant potential in short-distance optical communications, microscopic endoscopy, and optical power transmission. However, modal dispersion causes interference and crosstalk in spatially multiplexed optical signals during transmission, affecting demodulation performance. To address this challenge, researchers have proposed various demodulation techniques, including phase conjugation and transmission matrix methods. Yet these approaches have not fully met the demands of the information age for high fidelity, interference resistance, and high-speed transmission. In multimode fiber optical information transmission systems, deep neural networks have proven effective in overcoming multiple scattering issues, enabling precise information transmission. This paper summarizes the research progress of multimode optical information transmission technologies based on deep learning, including high fidelity, high speed, anti disturbance, multi-dimensional and physical prior enhanced optical information transmission, and discusses the optimization of key parameters of the system. At the same time, the opportunities and challenges of this technology in the future are prospected.