Depth estimation is a research area in computer vision that focuses on estimating the depth or distance of objects within a scene from a 2D image or sequence of images. This is a fundamental task in understanding the 3D structure of a scene and is important for various applications such as autonomous driving, robotics, augmented reality, and virtual reality. Researchers in this field develop algorithms and models that can accurately estimate the depth information from monocular images, stereo image pairs, or even videos. These algorithms often rely on techniques such as disparity estimation, optical flow, deep learning, and geometric methods to infer depth information from visual data. The ultimate goal of depth estimation research is to enable machines to perceive and interact with the world in a more human-like manner.