This work investigates how to use robust optimal transport (OT) solvers for shape matching. Specifically, we show how solutions of the OT problem benefit optimization-based and deep-network point cloud registration approaches, boosting accuracy at an affordable computational cost. We first give a practical overview of recent computational optimal transport approaches. We then provide solutions to the main difficulties in using these tools for shape matching. Finally, we showcase the performance…