June 2024: 🥳 Our work on standard codecs for deep vision models won the Best Student Paper Award @ the AIS Workshop (CVPRW 2024).

April 2024: 📑 Two papers have been accepted to CVPRW 2024.

February 2024: 👨‍🔧 Started my ELLIS Ph.D. at CVG (Daniel Cremers)

January 2024: 🥳 I was recognized as an outstanding reviewer at WACV 2024.

August 2023: 📑 Our paper Differentiable JPEG: The Devil is in the Details has been accepted to WACV 2024.

August 2023: 📑 Our paper The TYC Dataset for Understanding Instance-Level Semantics and Motions of Cells in Microstructures has been accepted to ICCVW 2023.

April 2023: 📑 Two papers An Instance Segmentation Dataset of Yeast Cells in Microstructures and On the Atrial Fibrillation Detection Performance of ECG-DualNet have been accepted to EMBC 2023.

July 2022:👨‍🔧 I started a research internship at NEC Laboratories America (Princeton).

June 2022: 📑 Our journal article has been accepted to appear in Physiological Measurement.

June 2022: 🥳 I got awarded a Lightning AI Travel Scholarship to visit the 2022 Lightning AI DevCon in NYC.

June 2022: 🥳 I was awarded the Papers with Code (Meta AI) Contributor Award.

I'm an ELLIS Ph.D. student at CVG. My research focuses on unsupervised scene understanding and self-supervised learning. I'm supervised by Daniel Cremers (CVG), Stefan Roth (Visual Inference Lab, TU Darmstadt), and Christian Rupprecht (Visual Geometry Group, University of Oxford). Prior to my Ph.D., I did research at NEC Laboratories America (Princeton), the Self-Organizing Systems Lab (TU Darmstadt; Heinz Koeppl), and the Artificial Intelligent Systems in Medicine Lab (TU Darmstadt; Christoph Hoog Antink).

I received a bachelor's in Information Systems Technology (computer science U electrical engineering) and a master's in Autonomous Systems (computer science) from TU Darmstadt. During my bachelor, I work as a working student at Bosch and as a teaching assistant at the mathematics department (TU Darmstadt) and the E5 Lab (TU Darmstadt).

I'm interested in unsupervised scene understanding (in 2D, 3D, and 4D), scene/optical flow as well as depth estimation, and self-supervised representation learning. Feel free to reach out if you would like to discuss research ideas.

I am open to supervising ambitious and talented Master's and Bachelor's students for their thesis. If you want to work with me, please send me an email describing the area/project you would like to work on. Please also attach your CV and up-to-date transcript.

Full publication list

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Journal Articles
2022
[]		Exploring Novel Algorithms for Atrial Fibrillation Detection by Driving Graduate Level Education in Medical Machine Learning (M Rohr, C Reich, A Höhl, T Lilienthal, T Dege, F Plesinger, V Bulkova, GD Clifford, MA Reyna and C Hoog Antink), In Physiological Measurement, IOP Publishing, volume 43, 2022.  [bibtex]
[]		Yeast cell segmentation in microstructured environments with deep learning (T Prangemeier, C Wildner, AO. Françani, C Reich and H Koeppl), In Biosystems, Elsevier, volume 211, 2022.  [bibtex]
Conference and Workshop Papers
2024
[]		A Perspective on Deep Vision Performance with Standard Image and Video Codecs (C Reich, O Hahn, D Cremers, S Roth and B Debnath), In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW), 2024.  [bibtex] [arXiv:2404.12330]
[]		Deep Video Codec Control (C Reich, B Debnath, D Patel, T Prangemeier, D Cremers and S Chakradhar), In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW), 2024.  [bibtex] [arXiv:2308.16215]
[]		Differentiable JPEG: The Devil is in the Details (C Reich, B Debnath, D Patel and S Chakradhar), In IEEE/CVF Winter Conference on Applications of Computer Vision (WACV), 2024. ([project page]) [bibtex] [arXiv:2309.06978]
2023
[]		Transformer Network with Time Prior for Predicting Clinical Outcome from EEG of Cardiac Arrest Patients (M Rohr, T Schilke, L Willems, C Reich, S Dill, G Güney and C Hoog Antink), In 50th Computing in Cardiology Conference (CinC), 2023.  [bibtex]
[]		On the Atrial Fibrillation Detection Performance of ECG-DualNet (C Reich, M Rohr, T Kircher and C Hoog Antink), In 45th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), 1-Page Paper, medRxiv, 2023.  [bibtex]
[]		The TYC Dataset for Understanding Instance-Level Semantics and Motions of Cells in Microstructures (C Reich, T Prangemeier and H Koeppl), In IEEE/CVF International Conference on Computer Vision Workshops (ICCVW), 2023. ([project page]) [bibtex] [arXiv:2304.07597]
[]		An Instance Segmentation Dataset of Yeast Cells in Microstructures (C Reich, T Prangemeier, AO Françani and H Koeppl), In 45th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), 2023. ([project page]) [bibtex] [arXiv:2304.07597]
2022
[]		Histopathological Image Classification based on Self-Supervised Vision Transformer and Weak Labels (AG Gul, O Cetin, C Reich, N Flinner, T Prangemeier and H Koeppl), In Medical Imaging 2022: Digital and Computational Pathology, Proceedings of SPIE, volume 12039, 2022.  [bibtex] [arXiv:2210.09021]
2021
[]		OSS-Net: Memory Efficient High Resolution Semantic Segmentation of 3D Medical Data (C Reich, T Prangemeier, Ö Cetin and H Koeppl), In British Machine Vision Conference (BMVC), 2021. ([project page]) [bibtex] [arXiv:2110.10640]
[]		Multi-StyleGAN: Towards Image-Based Simulation of Time-Lapse Live-Cell Microscopy (C Reich, T Prangemeier, C Wildner and H Koeppl), In International Conference on Medical image computing and computer-assisted intervention (MICCAI), 2021. ([project page]) [bibtex] [arXiv:2106.08285]
2020
[]		Multiclass Yeast Segmentation in Microstructured Environments with Deep Learning (T Prangemeier, C Wildner, AO. Françani, C Reich and H Koeppl), In 2020 IEEE Conference on Computational Intelligence in Bioinformatics and Computational Biology (CIBCB), 2020.  [bibtex] [arXiv:2011.08062]
[]		Attention-Based Transformers for Instance Segmentation of Cells in Microstructures (T Prangemeier, C Reich and H Koeppl), In 2020 IEEE International Conference on Bioinformatics and Biomedicine (BIBM), 2020.  [bibtex] [arXiv:2011.09763]