Abstract: Depth estimation from a single image is an important technology in the image-based depth acquisitionfor 3D reconstruction, which is also a classical problem in computer vision. Recently, supervisedlearning based depth estimation from a single image develops rapidly. In this paper, the recent related literaturesare reviewed and supervised learning based depth estimation from a single image and its model andoptimization are introduced. The current research situations of the parametric learning method, non-parametriclearning method and deep learning method both in domestic and abroad are analyzed respectively with theiradvantages and disadvantages. At last, summarizing these methods leads to the conclusion that depth estimationfrom a single image in deep learning framework is the development trend and research priority in thefuture.