Background and activities

Rudolf Mester has been head of the Visual Sensorics and Information Processing Lab at Goethe University, Frankfurt, since 2004, after having had positions in the Physics department of U Frankfurt, and in Bosch Corporate Research.
Since October 2018, he is with the Computer Science Dept. (IDI) at NTNU Trondheim, Full Professor (DNV GL endowment), and member of the Norwegian Open AI Lab.
In the recent decade, he lead research initiatives and projects for intelligent visual vehicle sensorics, for applications of AI in mobile systems, visual surround sensing for autonomous driving, and machine learning for ‘trainable vehicles’ and vehicle control.

Besides these application-oriented topics, he performs fundamental research in the performance analysis of AI methods, assurance of machine learning algorithms, and in the foundations of robust and reliable perception and planning algorithms building on estimation theory, control theory, and machine learning.
At NTNU, Rudolf Mester focuses on performance, confidence quantification, and assurance of AI / machine learning methods, on classical and ML-based perception approaches for intelligent machines, and on autonomous systems, on the road, on and under water, and in the air.
The support from DNV GL reflected in this endowment professorship and in good cooperation is acknowledged and appreciated.

Scientific, academic and artistic work


  • Teigen, Andreas Langeland; Saad, Aya; Mester, Rudolf; Stahl, Annette. (2021) Few-Shot Open World Learner. IFAC-PapersOnLine.
  • Zwilgmeyer, Peder Georg Olofsson; Yip, Mauhing; Teigen, Andreas Langeland; Mester, Rudolf; Stahl, Annette. (2021) The VAROS Synthetic Underwater Data Set: Towards realistic multi-sensor underwater data with ground truth. IEEE International Conference on Computer Vision (ICCV).
  • Hukkelås, Håkon; Mester, Rudolf; Lindseth, Frank. (2021) Image Inpainting with Learnable Feature Imputation. Pattern Recognition, 42nd DAGM German Conference.
  • Namazi, Elnaz; Mester, Rudolf; Lu, Chaoru; Li, Jingyue. (2021) Geolocation estimation of target vehicles using neural network-based image processing and geometric computations. 2021.
  • Namazi, Elnaz; Mester, Rudolf; Lu, Chaoru; Log, Markus Metallinos; Li, Jingyue. (2021) Improving vehicle localization with two low-cost GPS receivers. 2021.




  • Fanani, Nolang; Ochs, Matthias; Stürck, Alina; Mester, Rudolf. (2018) CNN-based multi-frame IMO detection from a monocular camera. IEEE conference proceedings. 2018. ISBN 978-1-5386-4452-2.
  • Ochs, Matthias; Bradler, Henry; Mester, Rudolf. (2018) Spatio-Temporal Depth Interpolation (STDI). IEEE conference proceedings. 2018. ISBN 978-1-5386-4452-2.