The goal of this project is to explore generative neural approaches to create synthetic image data needed to build and optimize a visual search index. The SynthNet solution approach consists of synthetically generating all required comparison images from a real-world industry grade 3D CAD data and using them for object identification. For each component, a set of views of an object is automatically generated synthetically under different lighting and material conditions.

Further information:


  • Berliner Hochschule für Technik (BHT)
  • Nyris GmbH, Berlin
  • topex GmbH, Erkenbrechtsweiler


Funded by:


Contact at the BHT:

Prof. Dr. Kristian Hildebrand