3D Scene Reconstruction for Modeling & Mapping

Our Mission

ISPRS Working Group II/3 aims to make progress in the automatic recognition and 3D reconstruction of objects in complex scenes from images, point clouds, and other sensor data. The emphasis is on scenes characterized by the occurrence of different object classes, e.g. urban scenes including vegetation, buildings, roads, street furniture, cars and pedestrians, or indoor scenes including furniture and different types of objects. One of the main applications of interest of our WG is the generation of high-resolution 3D City Models, but the scope of the WG also includes any form of object detection in complex environments, e.g. in the context of robotics or autonomous driving. It is also our goal to evaluate methods for object extraction and the suitability of different sensors for that task.

To this purpose, the WG organizes workshops to exchange the latest developments on object recognition and reconstruction, collaborating closely with other WGs both from TC II and from other TCs. Furthermore, the WG strives to organize at least one benchmark related to its scope, and it intends to contribute to Theme Issues of journals published by the ISPRS or other journals related to the field.


Working Group Officers


Ksenia Bittner , ChairKsenia Bittner
German Aerospace Center (DLR)
Earth Observation Center (EOC)
Remote Sensing Technology Institute,
Photogrammetry and Image Analysis
82234 Weßling
+49 8153 28 4285



Franz Rottensteiner , Co-ChairFranz Rottensteiner
Institute of Photogrammetry and GeoInformation
Leibniz University Hannover
Nienburger Straße 1
30167 Hannover
+49 511 762 3893



Friedrich Fraundorfer , Co-ChairFriedrich Fraundorfer
Institute of Computer Graphics and Vision
Graz University of Technology
Inffeldgasse 16/II
8010 Graz
+43 316 873 5020



Max Mehltretter, SecretaryMax Mehltretter
Institute of Photogrammetry and GeoInformation
Leibniz University Hannover
Nienburger Straße 1
30167 Hannover
+49 511 762 2981



Jinha Jung, SupporterJinha Jung
Lyles School of Civil Engineering
Purdue University
550 Stadium Mall Drive
West Lafayette, IN 47907-2051
+1 765 496 1267


Arpan Kusari, SupporterArpan Kusari
University of Michigan Transportation Research Institute
University of Michigan
2901 Baxter Road,
Ann Arbor, MI 48109
+1 734 763 4806


Martin Weinmann, SupporterMartin Weinmann
Institute of Photogrammetry and Remote Sensing
Karlsruhe Institute of Technology (KIT)
Englerstraße 7
76131 Karlsruhe
+49 721 608 47302


Terms of Reference

  • Models and techniques for extracting features, geometrical primitives and objects from data acquired by airborne, spaceborne and/or terrestrial sensors, including object detection and 3D object reconstruction in complex scenes.
  • Semantic interpretation of data of various origins and generated by various sensors, including methods for semantic segmentation and panoptic segmentation, potentially involving an interpretation of the entire scene, and considering both outdoor and indoor environments.
  • Integration of semantic interpretation and 3D reconstruction of complex scenes, including point-based methods and methods based on object models, e.g. using implicit representations.
  • Generation and update of high-resolution 3D city models and road databases, including mesh based, polyhedral, parametric and multi-scale representations possibly with level-of-detail (LOD) and (semantic) attributes, and texturing of the resultant 3D models.
  • Object detection, recognition and 3D reconstruction in the context of robotics or autonomous driving.
  • Multi-modal data fusion: performing any of the tasks mentioned above by exploiting the complementarity of using different viewpoints (space-borne, nadir/oblique aerial, UAV, fixed/mobile terrestrial), different sensor types (mono-scopic/stereoscopic images, LiDAR, (In)SAR), and existing data (traditional cartographic products, CAD models, urban GIS, data produced by crowd-sourcing).
  • Methods addressing any of the tasks mentioned above, while focusing on handling noisy or out-of-distribution input data, including techniques for uncertainty estimation and uncertainty propagation.









The International Society for Photogrammetry and Remote Sensing is a non-governmental organization devoted to the development of international cooperation for the advancement of photogrammetry and remote sensing and their applications. The Society operates without any discrimination on grounds of race, religion, nationality, or political philosophy.

Our Contact

Leibniz University Hannover
Institute of Photogrammetry and GeoInformation
Nienburger Str. 1
D-30167 Hannover