Discrete Inference and Learning in Artificial Vision

This course presents the state of the art energy minimization algorithms that are used to perform inference in modern artificial vision models: that is, efficient methods for obtaining the most likely interpretation of a given visual input. We will also cover the popular max-margin framework for estimating the model parameters using inference.

This course provides deep details on Graph Cuts.