Human pose estimation is a basic and challenging task in the field of computer vision. It is the basis for many of computer vision tasks, such as action recognition and action detection. With the development of deep learning methods, deep learning-based human pose estimation algorithms have shown excellent results. This study divides pose estimation methods into three categories, including single person pose estimation, top-down multi-person pose estimation, and bottom-up multi-person pose estimation. The development of 2D human pose estimation algorithms in recent years is introduced, and the current challenges of two-dimensional human pose estimation are discussed. Finally, the outlook for the future development of human pose estimation is given.