Deep Stereo

Supervision: Christian Rupprecht, Federico Tombari

In this project we aim at developing a method for learning how to predict stereo disparities from a pair of images. We will start from the analysis of a recently published method (Zbontar and LeCun^?, 15), and investigate different aspects aimed at improving this approach in terms of accuracy and efficiency. Another important goal of the project is to experimentally evaluate how learned disparities can deal with noisy images under realistic working conditions.

For further information please contact: Christian Rupprecht