  Indirect Time-of-Flight cameras (iToF) are low-cost devices that provide
depth images at an interactive frame rate. However, they are affected by
different error sources, with the spotlight taken by Multi-Path Interference
(MPI), a key challenge for this technology. Common data-driven approaches tend
to focus on a direct estimation of the output depth values, ignoring the
underlying transient propagation of the light in the scene. In this work
instead, we propose a very compact architecture, leveraging on the
direct-global subdivision of transient information for the removal of MPI and
for the reconstruction of the transient information itself. The proposed model
reaches state-of-the-art MPI correction performances both on synthetic and real
data and proves to be very competitive also at extreme levels of noise; at the
same time, it also makes a step towards reconstructing transient information
from multi-frequency iToF data.
