Semantics 3D

Semantics 3D

Automated 3D reconstruction and extraction of semantic information from images and image sequences is an important topic of research in Photogrammetry, Remote Sensing, GIS, and Computer Vision. Semantics3D is a workshop that follows a series of earlier ISPRS events related to photogrammetric 3D reconstruction (PhotoGA), automatic object detection for city models, road databases and traffic analysis (CMRT), and image sequence analysis (ISA). The workshop will bring together experts from the above-mentioned fields to discuss recent developments, the potential of various data sources, and future trends in 3D reconstruction and information extraction from imagery. Its focus is on methodological research. The workshop will be part of the ISPRS Geospatial Week 2021 and is hosted by the Mohammed Bin Rashid Space Centre (MBRSC) in parallel with a number of related geospatial workshops. The event will be held as a two-day single track workshop of oral presentations and poster sessions.


Franz Rottensteiner, Leibniz Universität Hannover, Germany

Michael Ying Yang, University of Twente, the Netherlands
Themes of Event
  • Automatic detection and 3D reconstruction of objects using data from terrestrial, airborne or satellite sensors
  • Supervised classification techniques for applications to 3D scenes, in particular deep learning for 3D scene analysis
  • Large-scale scene analysis
  • Classification and semantic segmentation of point clouds and surface meshes with or without radiometric information
  • Object detection, recognition and 3D reconstruction in the context of robotics or autonomous driving
  • Integration of data from multiple viewpoints or multiple sensors for automated object detection and reconstruction
  • Integration of existing interpreted data such as existing maps or urban GIS for object detection and reconstruction
  • Methods for the generation and update of high-resolution 3D city models and road databases
  • Automatic texturing of 3D city models
  • Evaluation of techniques for automated scene analysis
  • Detection and tracking of objects in image sequences and videos

Scientific Committee

  • Ahmed Alamouri, Technische Universität Braunschweig, Germany
  • Claus Brenner, Leibniz Universtität Hannover, Germany
  • Ian Cherabier, ETH Zurich, Switzerland
  • Andrea Fusiello, University of Udine, Italy
  • Markus Gerke, Technische Universität Braunschweig, Germany
  • Norbert Haala, University of Stuttgart, Germany
  • Petra Helmholz, Curtin University, Australia
  • Ludwig Hoegner, Technische Universitaet Muenchen, Germany
  • Siavash Hosseinyalamdary, University of Twente, The Netherlands
  • Mehdi Maboudi, Technische Universität Braunschweig, Germany
  • Clément Mallet, Institut Géographique National (IGN), France
  • Eleonora Masset, University of Udine, Italy
  • Martin Oswald, ETH Zurich, Switzerland
  • José Pena, Institute of Agricultural Sciences, CSIC, Spain
  • Rongjun Qin, The Ohio State University, USA
  • Camillo Ressl, Vienna University of Technology, Austria
  • Audrey Richard, ETH Zurich, Switzerland
  • Ribana Roscher, University of Bonn, Germany
  • Mathias Rothermel, ETH Zurich, Switzerland
  • Franz Rottensteiner, Leibniz Universität Hannover, Germany
  • Vasit Sagan, St. Louis University, USA
  • Konrad Schindler, ETH Zurich, Switzerland
  • Mozdeh Shabasi, University of Calgary, Canada
  • Jie Shan, Purdue University, USA
  • Uwe Stilla, Technische Universitaet Muenchen, Germany
  • Devis Tuia, Wageningen University, The Netherlands
  • Bruno Vallet, Institut Géographique National (IGN), France
  • Yury Vizilter, State Research Institute of Aviation Systems, Russia
  • Michele Volpi, ETH Zurich, Switzerland
  • Ruisheng Wang, University of Calgary, Canada
  • Jan Dirk Wegner, ETH Zurich, Switzerland
  • Martin Weinmann, Karlsruhe Institute of Technology, Germany
  • Bo Wu, The Hong Kong Polytechnic University, Hong Kong
  • Alper Yilmaz, The Ohio State University, USA