We present a novel, data driven approach for solving the problem of registration of two point
cloud scans. Our approach is direct in the sense that a single pair of corresponding local
patches already provides the necessary transformation cue for the global registration. To
achieve that, we first endow the state of the art PPF-FoldNet auto-encoder (AE) with a pose-
variant sibling, where the discrepancy between the two leads to pose-specific descriptors.
Based upon this, we introduce RelativeNet, a relative pose estimation network to assign …

Does multi-task training scheme help to boost the feature quality? In order to find out how
multi-task training affects the quality of the learned intermediate features, we trained several
networks with combinations of different supervision signals. For the sake of controlled
experimentation, all networks are made to have the identical architecture. They are trained
with the same data for 10 epochs. Hence, the only variable remains to be the objective
function used for each group. In total, there are four networks to be compared. The first one …