SGPN: Similarity Group Proposal Network for 3D Point Cloud Instance Segmentation

We introduce Similarity Group Proposal Network (SGPN), a simple and intuitive deep learning framework for 3D object instance segmentation on point clouds. SGPN uses a single network to predict point grouping proposals and a corresponding semantic class for each proposal, from which we can directly extract instance segmentation results. Important to the effectiveness of SGPN is its novel representation of 3D instance segmentation results in the form of a similarity matrix that indicates the similarity between each pair of points in embedded feature space, thus producing an accurate grouping proposal for each point. To the best of our knowledge, SGPN is the first framework to learn 3D instance-aware semantic segmentation on point clouds. Experimental results on various 3D scenes show the effectiveness of our method on 3D instance segmentation, and we also evaluate the capability of SGPN to improve 3D object detection and semantic segmentation results. We also demonstrate its flexibility by seamlessly incorporating 2D CNN features into the framework to boost performance

Erkenntnisse der neueren Unterrichtsforschung zum Fremdsprachenunterricht

Nachdem dem Fremdsprachenunterricht in der empirischen Schulleistungsforschung lange Zeit eher geringe Aufmerksam zuteil wurde, liefern Studien wie LAU oder DESI mittlerweile wichtige Befunde zu den Schulleistungen und der Unterrichtsqualität im Fremdsprachenbereich. Im vorliegenden Beitrag soll anhand von ausgewählten Beispielen ein knapper Einblick in Fragestellungen, Forschungsdesigns und Befunde jüngerer empirischer Bildungsforschung zum Fremdsprachenunterricht gegeben werden

Local transport measurements on epitaxial graphene

Growth of large-scale graphene is still accompanied by imperfections. By means of a four-tip STM/SEM the local structure of graphene grown on SiC(0001) was correlated with scanning electron microscope images and spatially resolved transport measurements. The systematic variation of probe spacings and substrate temperature has clearly revealed two-dimensional transport regimes of Anderson localization as well as of diffusive transport. The detailed analysis of the temperature dependent data demonstrates that the local on-top nano-sized contacts do not induce significant strain to the epitaxial graphene films.Comment: 3 figure