Institut für Informationsverarbeitung (TNT) - Homepage of Christoph Reinders

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.

Publications

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
(Link) BibTeX
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, September 2023
(pdfGithub) BibTeX
Timo Kaiser, Christoph Reinders, Bodo Rosenhahn
Compensation Learning in Semantic Segmentation
Computer Vision and Pattern Recognition Workshops (CVPRW) , June 2023
(pdf, pdfGithub, Arxiv.org) BibTeX
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
(pdfGithub, Final Paper) BibTeX
Timo Kaiser, Lukas Ehmann, Christoph Reinders, Bodo Rosenhahn
Blind Knowledge Distillation for Robust Image Classification
arXiv, arXiv, November 2022
(pdfArxiv.org) BibTeX
Maximilian Schier, Christoph Reinders, Bodo Rosenhahn
Constrained Mean Shift Clustering
Proceedings of the 2022 SIAM International Conference on Data Mining (SDM), SIAM, April 2022
(pdfGithub) BibTeX
Christoph Reinders, Frederik Schubert, Bodo Rosenhahn
ChimeraMix: Image Classification on Small Datasets via Masked Feature Mixing
Proceedings of the Thirty-First International Joint Conference on Artificial Intelligence (IJCAI), 2022
(Arxiv.org, Github) BibTeX
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
(Link) BibTeX
Christoph Reinders, Bodo Rosenhahn
Adversarial Attacks and Defenses in Deep Learning
We Are Developers!, 2022
BibTeX
Christoph Reinders, Bodo Rosenhahn
Neuronale Netze: Angriffe und Verteidigung - Ich sehe was, was du nicht siehst
iX Developer 2020 – Machine Learning 2.0, 2020
BibTeX
Christoph Reinders and Bodo Rosenhahn
Neural Random Forest Imitation
arXiv, November 2019
(Arxiv.org) BibTeX
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
BibTeX
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
(pdf) BibTeX
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
(pdfArxiv.org) BibTeX
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
(DOI) BibTeX

Research topics

COVMAP-Dataset