Christoph Reinders, M.Sc.
Leibniz Universität Hannover
Schneiderberg 32
30167 Hannover
phone: +49 511 762-5006
office location: room 244

Christoph Reinders studied Computer Science at Leibniz Universität Hannover. For his Bachelor's thesis – "Handwriting Recognition On-The-Fly" – he was awarded the "Studienpreis 2014 des VDE Hannover". In the winter of 2014 he studied at the University of California, Berkeley, as a visiting student researcher and conducted research with Professor Alexei Efros on interactive editing during photo-capture for an iPad app.

Throughout his Master he focused on image processing and machine learning and graduated in October 2017. His Master's thesis, "Deep-Learning based Road Type Classification", deals with training fully convolutional networks with very little data by combining random forests and convolutional neural networks. Since November 2017, he has been working towards his PhD at the Institut für Informationsverarbeitung (TNT). His main research interests are deep learning and image processing.

Research topics

  • Convolutional Neural Networks / Deep Learning
  • Semantic Segmentation for Autonomous Driving
  • Random Forests
  • App Development (e.g. iOS)
  • Image processing

If you are interested in any of these topics for a student position, bachelor's thesis, or master's thesis, feel free to contact me.


Show selected publications only
  • Christoph Reinders, Michael Ying Yang, Bodo Rosenhahn
    Two Worlds in One Network: Fusing Deep Learning and Random Forests for Classification and Object Detection
    Volunteered Geographic Information, Springer Nature Switzerland, 2024
  • Maximilian Schier, Christoph Reinders, Bodo Rosenhahn
    Learned Fourier Bases for Deep Set Feature Extractors in Automotive Reinforcement Learning
    2023 IEEE 26th International Conference on Intelligent Transportation Systems (ITSC), IEEE, p. to appear, September 2023
  • Timo Kaiser, Christoph Reinders, Bodo Rosenhahn
    Compensation Learning in Semantic Segmentation
    Computer Vision and Pattern Recognition Workshops (CVPRW) , June 2023
  • Maximilian Schier, Christoph Reinders, Bodo Rosenhahn
    Deep Reinforcement Learning for Autonomous Driving Using High-Level Heterogeneous Graph Representations
    2023 IEEE International Conference on Robotics and Automation (ICRA), IEEE, pp. 7147-7153, 2023
  • Timo Kaiser, Lukas Ehmann, Christoph Reinders, Bodo Rosenhahn
    Blind Knowledge Distillation for Robust Image Classification
    arXiv, arXiv, November 2022
  • Maximilian Schier, Christoph Reinders, Bodo Rosenhahn
    Constrained Mean Shift Clustering
    Proceedings of the 2022 SIAM International Conference on Data Mining (SDM), SIAM, April 2022
  • Christoph Reinders, Frederik Schubert, Bodo Rosenhahn
    ChimeraMix: Image Classification on Small Datasets via Masked Feature Mixing
    31st International Joint Conference on Artificial Intelligence and the 25th European Conference on Artificial Intelligence (IJCAI-ECAI), 2022
  • Kai Cordes, Christoph Reinders, Paul Hindricks, Jonas Lammers, Bodo Rosenhahn, Hellward Broszio
    RoadSaW: A Large-Scale Dataset for Camera-Based Road Surface and Wetness Estimation
    2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW), 2022
  • Christoph Reinders, Bodo Rosenhahn
    Adversarial Attacks and Defenses in Deep Learning
    We Are Developers!, 2022
  • Christoph Reinders, Bodo Rosenhahn
    Neuronale Netze: Angriffe und Verteidigung - Ich sehe was, was du nicht siehst
    iX Developer 2020 – Machine Learning 2.0, 2020
  • Christoph Reinders and Bodo Rosenhahn
    Neural Random Forest Imitation
    arXiv, November 2019
  • Christoph Reinders, Hanno Ackermann, Michael Ying Yang, Bodo Rosenhahn
    Learning Convolutional Neural Networks for Object Detection with very little Training Data
    Multimodal Scene Understanding, Academic Press, 2019, edited by Michael Ying Yang, Bodo Rosenhahn and Vittorio Murino
  • Florian Kluger, Christoph Reinders, Kevin Raetz, Philipp Schelske, Bastian Wandt, Hanno Ackermann, Bodo Rosenhahn
    Region-based Cycle-Consistent Data Augmentation for Object Detection
    2018 IEEE International Conference on Big Data, December 2018
  • Christoph Reinders, Hanno Ackermann, Michael Ying Yang, Bodo Rosenhahn
    Object Recognition from very few Training Examples for Enhancing Bicycle Maps
    2018 IEEE Intelligent Vehicles Symposium (IV), June 2018
  • Christoph Reinders, Florian Baumann, Björn Scheuermann, Arne Ehlers, Nicole Mühlpforte, Alfred O. Effenberg, Bodo Rosenhahn
    On-The-Fly Handwriting Recognition using a High-Level Representation
    The 16th International Conference on Computer Analysis of Images and Patterns (CAIP), Valetta, Malta, September 2015
Other activities



The training and test dataset used in "Object Recognition from very few Training Examples for Enhancing Bicycle Maps" is available upon request.