|M. Pawan Kumar|
EFFICIENT FRANK-WOLFE FOR DENSE CRFs AND PIECEWISE LINEAR CNNs
M. Pawan Kumar
Pre-Doc Summer School, ETH Zurich, 2017
The course consists of two parts. In the first part, we will consider the challenging problem of energy minimization in dense CRFs, which is typically addressed using the mean-field algorithm. The popularity of mean-field is largely due to the fact that each iteration of the algorithm can be performed efficiently using a filtering method based on the permutohedral lattice. We will consider several continuous relaxations for the problem, which provide strong theoretical guarantees on the quality of the solution, and show that they can also be solved efficiently by leveraging the power of the Frank-Wolfe algorithm. Specifically, each iteration of Frank-Wolfe can also be performed efficiently using the same filtering method.
Topic 1: Dense CRF [PPT] [PDF]