In this paper we address the problem of reconstructing a structurally simple surface representation from point datasets of scanned scenes as they occur for instance in city scanning projects. Such datasets generally suffer from all kinds of scanning artifacts including noise, outliers, holes and irregular/anisotropic sampling. Most common surface reconstruction methods fail due to these shortco...

Recently, fitted Q-iteration (FQI) based methods have become more popular due to their increased sample efficiency, a more stable learning process and the higher quality of the resulting policy. However, these methods remain hard to use for continuous action spaces which frequently occur in real-world tasks, e.g., in robotics and other technical applications. The greedy action selection commonl...

In this paper, we propose a locality-constrained and sparsity-encouraged manifold fitting approach, aiming at capturing the locally sparse manifold structure into neighborhood graph construction by exploiting a principled optimization model. The proposed model formulates neighborhood graph construction as a sparse coding problem with the locality constraint, therefore achieving simultaneous nei...