In this project, we are exploring the application of machine learning to solving the classical stereoscopic correspondence problem. We present a re-implementation of several state-of-the-art stereo correspondence methods. Additionally, we present new methods, replacing one of the state-of-the-art methods for stereo with a proposed technique based on machine learning methods. These new methods out-perform existing heuristic baselines significantly.

CS231A Paper

Source Code