Dr. rer. nat. Sven Sickert
Sven Sickert
Address: Computer Vision Group
Department of Mathematics and Computer Science
Friedrich Schiller University of Jena
Ernst-Abbe-Platz 2
07743 Jena
Germany
Phone: +49 (0) 3641 9 46424
E-mail: sven (dot) sickert (at) uni-jena (dot) de
Room: 1211
Links: GoogleScholar, Mastodon, ORCID
Curriculum Vitae
since 2019 Research Associate
Computer Vision Group, Friedrich Schiller University Jena
since 2019 Lecturer & Study Program Coordinator for Computer Science studies
Institute for Computer Science Jena, Friedrich Schiller University Jena
2019 – 2022 Team Leader: “Learning from 3D and Unstructured Data”
Computer Vision Group, Friedrich Schiller University Jena
2013 – 2018 PhD Student
Computer Vision Group, Friedrich Schiller University Jena
PhD Thesis: “Semantic Segmentation of 3D Data using Contextual Cues”
2007 – 2012 Studies in Computer Science (Diploma)
Friedrich Schiller University Jena
Focus: Image Processing / Computer Vision
Diploma Thesis: “Strategien des Aktiven Lernens” (“Strategies in Active Learning”)
Research Interests
  • 3D Point Cloud Analysis
  • Representation Learning
  • Semantic Segmentation
  • Medical Image Understanding
Projects
Ongoing
Former
Reviewer Activities
Journals
  • IEEE Transactions on Image Processing
  • Expert Systems With Applications
  • Remote Sensing
Conferences & Workshops
  • Asian Conference on Computer Vision (ACCV, 2022)
  • UK Conference on Medical Image Understanding and Analysis (MIUA, 2020)
  • Special Session on Machine Learning in Advanced Machine Vision (AMV) at ICMLA 2019
Teaching
Summer term 2024
Winter term 2023/2024
Supervised Theses
  • Maria Gogolev: “Comparing and Modifying Distributions of Latent Diffusion Models to Impose Image Properties Niklas, Sven, Tim “. Master thesis, 2024. (joint supervision with Niklas Penzel and Tim Büchner)
  • Chris Gerlach: “Erkennung und Evaluierung von Kopfgesten und Mimiken in Videoaufnahmen im Kontext der Verhaltensanalyse”. Master thesis, 2023. (joint supervision with Tim Büchner)
  • Fateme Shafiei: “Classification of Facial Expression using Multivariate Surface Electromyography Timeseries”. Master thesis, 2022. (joint supervision with Tim Büchner)
  • Chima Nmerenu: “Learning Networks for 3D Point Cloud Data based on Synthetically Generated Samples from Mathematical Formulas”. Master thesis, 2021.
  • Xu Yang: “Spherical Convolutions at Anatomical Landmarks for Facial Analysis Tasks”. Master thesis, 2021. (joint supervision with Jhonatan Contreras)
  • Felix Fleisch: “3D-Momente Invarianten auf Basis gelernter Triangulierungen zur semantischen Analyse von 3D-Punktwolken”. Bachelor thesis, 2021.
  • Selina Müller: “Integrating Hierarchical Knowledge for Medical Image Analysis Tasks”. Master thesis, 2019. (joint supervision with Clemens-Alexander Brust)
  • David Pertzborn: “Application and Analysis of Generative Adversarial Network for Non-Supervised Anomaly Detection in Colonoscopy Imaging”. Master thesis, 2019. (joint supervision with Clemens-Alexander Brust and Christoph Theiß)
  • Marie Arlt: “Improving Semantic Segmentation of Polyps in Coloscopic Data using Augmentation Techniques”. Master thesis, 2019. (joint supervision with Clemens-Alexander Brust and Christoph Theiß)
  • Martin Nußbaum: “Semantische Segmentierung von sequenziellen Bilddaten mittels Rekurrenter Neuronaler Netze”. Bachelor thesis, 2017.
  • Christopher Manthey: “Fahrbahnsegmentierung mittels echtzeitfähiger Convolutional Networks in eingebetteten Systemen”. Master thesis, 2016.
  • Matthias Reuse: “Analyse verschiedener Demosaicing-Verfahren für Aufgaben der Fahrbahnerkennung”. Bachelor thesis, 2016. (joint supervision with Manuel Amthor)
  • Christoph Runge: “Semantische Segmentierung mittels Iterative Context Forests für große Mehrklassenprobleme”. Bachelor thesis, 2015.
  • Clemens-Alexander Brust: “Semantische Segmentierung mittels Convolutional Networks für die automatische Fahrbahnsegmentierung” Bachelor thesis, 2014. (joint supervision with Marcel Simon and Erik Rodner)

If you are interested in doing a Bachelor’s or Master’s thesis in the area of computer vision, also check out our page on Final Theses!

Publications
2024
Tim Büchner, Sven Sickert, Gerd F. Volk, Christoph Anders, Joachim Denzler, Orlando Guntinas-Lichius:
Reducing the Gap Between Mimics and Muscles by Enabling Facial Feature Analysis during sEMG Recordings [Abstract].
Congress of the Confederation of European ORL-HNS. 2024. (accepted)
[bibtex] [abstract]
Tim Büchner, Sven Sickert, Gerd F. Volk, Joachim Denzler, Orlando Guntinas-Lichius:
An Automatic, Objective Method to Measure and Visualize Volumetric Changes in Patients with Facial Palsy during 3D Video Recordings [Abstract].
95th Annual Meeting German Society of Oto-Rhino-Laryngology, Head and Neck Surgery e. V., Bonn. 2024.
[bibtex] [web] [doi] [abstract]
Tim Büchner, Sven Sickert, Gerd F. Volk, Martin Heinrich, Joachim Denzler, Orlando Guntinas-Lichius:
Measuring and Visualizing Volumetric Changes Before and After 10-Day Biofeedback Therapy in Patients with Synkinetic Facial Palsy Using 3D Video Recordings [Abstract].
Congress of the Confederation of European ORL-HNS. 2024. (accepted)
[bibtex] [abstract]
2023
Felix Schneider, Sven Sickert, Phillip Brandes, Sophie Marshall, Joachim Denzler:
Hard is the Task, the Samples are Few: A German Chiasmus Dataset.
Language Technology Conference: Human Language Technologies as a Challenge for Computer Science and Linguistics (LTC). 2023.
[bibtex] [abstract]
Tim Büchner, Sven Sickert, Gerd F. Volk, Christoph Anders, Orlando Guntinas-Lichius, Joachim Denzler:
Let’s Get the FACS Straight - Reconstructing Obstructed Facial Features.
International Conference on Computer Vision Theory and Applications (VISAPP). Pages 727-736. 2023.
[bibtex] [pdf] [web] [doi] [abstract]
Tim Büchner, Sven Sickert, Gerd F. Volk, Orlando Guntinas-Lichius, Joachim Denzler:
From Faces To Volumes - Measuring Volumetric Asymmetry in 3D Facial Palsy Scans.
International Symposium on Visual Computing (ISVC). Pages 121-132. 2023. Best Paper Award
[bibtex] [web] [doi] [abstract]
Tim Büchner, Sven Sickert, Roland Graßme, Christoph Anders, Orlando Guntinas-Lichius, Joachim Denzler:
Using 2D and 3D Face Representations to Generate Comprehensive Facial Electromyography Intensity Maps.
International Symposium on Visual Computing (ISVC). Pages 136-147. 2023.
[bibtex] [web] [doi] [code] [abstract]
2022
Felix Schneider, Sven Sickert, Phillip Brandes, Sophie Marshall, Joachim Denzler:
Metaphor Detection for Low Resource Languages: From Zero-Shot to Few-Shot Learning in Middle High German.
LREC Workshop on Multiword Expression (LREC-WS). Pages 75-80. 2022.
[bibtex] [web] [code] [abstract]
Tim Büchner, Sven Sickert, Gerd F. Volk, Orlando Guntinas-Lichius, Joachim Denzler:
Automatic Objective Severity Grading of Peripheral Facial Palsy Using 3D Radial Curves Extracted from Point Clouds.
Challenges of Trustable AI and Added-Value on Health. Pages 179-183. 2022.
[bibtex] [web] [doi] [code] [abstract]
2021
Martin Thümmel, Sven Sickert, Joachim Denzler:
Facial Behavior Analysis using 4D Curvature Statistics for Presentation Attack Detection.
IEEE International Workshop on Biometrics and Forensics (IWBF). Pages 1-6. 2021.
[bibtex] [web] [doi] [code] [abstract]
2020
Anish Raj, Oliver Mothes, Sven Sickert, Gerd F. Volk, Orlando Guntinas-Lichius, Joachim Denzler:
Automatic and Objective Facial Palsy Grading Index Prediction using Deep Feature Regression.
Annual Conference on Medical Image Understanding and Analysis (MIUA). Pages 253-266. 2020.
[bibtex] [pdf] [web] [doi] [abstract]
Jhonatan Contreras, Sven Sickert, Joachim Denzler:
Region-based Edge Convolutions with Geometric Attributes for the Semantic Segmentation of Large-scale 3D Point Clouds.
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing. 13 (1) : pp. 2598-2609. 2020.
[bibtex] [pdf] [web] [doi] [abstract]
2019
Andreas Dittberner, Sven Sickert, Joachim Denzler, Orlando Guntinas-Lichius:
Intraoperative Online Image-guided Biopsie on the Basis of a Deep Learning Algorithm to the Automatic Detection of Head and Neck Carcinoma by Means of Real Time Near-Infrared ICG Fluorescence Endoscopy.
Laryngo-Rhino-Otologie. 98 (S02) : pp. 115. 2019.
[bibtex] [web] [doi]
Jhonatan Contreras, Sven Sickert, Joachim Denzler:
Automatically Estimating Forestal Characteristics in 3D Point Clouds using Deep Learning.
iDiv Annual Conference. 2019. Poster
[bibtex] [web] [abstract]
Marie Arlt, Jack Peter, Sven Sickert, Clemens-Alexander Brust, Joachim Denzler, Andreas Stallmach:
Automated Polyp Differentiation on Coloscopic Data using Semantic Segmentation with CNNs.
Endoscopy. 51 (04) : pp. 4. 2019.
[bibtex] [web] [doi] [abstract]
2018
Andreas Dittberner, Sven Sickert, Joachim Denzler, Orlando Guntinas-Lichius, Thomas Bitter, Sven Koscielny:
Development of an Automatic Image Analysis Method by Deep Learning Methods for the Detection of Head and Neck Cancer Based on Standard Real-Time Near-Infrared ICG Fluorescence Endoscopy Images (NIR-ICG-FE).
Laryngo-Rhino-Otologie. 97 (S02) : pp. 97. 2018.
[bibtex] [web] [doi] [abstract]
Niclas Schmitt, Sven Sickert, Orlando Guntinas-Lichius, Thomas Bitter, Joachim Denzler:
Automated MRI Volumetry of the Olfactory Bulb.
Laryngo-Rhino-Otologie. 97 (S02) : pp. 36. 2018.
[bibtex] [web] [doi] [abstract]
2017
Gianluca Tramontana, Martin Jung, Christopher R. Schwalm, Kazuhito Ichii, Gustau Camps-Valls, Botond Raduly, Markus Reichstein, M. Altaf Arain, Alessandro Cescatti, Gerard Kiely, Lutz Merbold, Penelope Serrano-Ortiz, Sven Sickert, Sebastian Wolf, Dario Papale:
Predicting Carbon Dioxide and Energy Fluxes with Empirical Approaches in FLUXNET.
European Geosciences Union General Assembly (EGU): Abstract + Poster Presentation. 2017.
[bibtex] [pdf] [web]
Sven Sickert, Joachim Denzler:
Semantic Segmentation of Outdoor Areas using 3D Moment Invariants and Contextual Cues.
DAGM German Conference on Pattern Recognition (DAGM-GCPR). Pages 165-176. 2017.
[bibtex] [pdf] [doi] [abstract]
2016
Clemens-Alexander Brust, Sven Sickert, Marcel Simon, Erik Rodner, Joachim Denzler:
Neither Quick Nor Proper -- Evaluation of QuickProp for Learning Deep Neural Networks.
2016. Technical Report TR-FSU-INF-CV-2016-01
[bibtex] [pdf] [abstract]
Gianluca Tramontana, Martin Jung, Christopher R. Schwalm, Kazuhito Ichii, Gustau Camps-Valls, Botond Raduly, Markus Reichstein, M. Altaf Arain, Alessandro Cescatti, Gerard Kiely, Lutz Merbold, Penelope Serrano-Ortiz, Sven Sickert, Sebastian Wolf, and Dario Papale:
Predicting Carbon Dioxide and Energy Fluxes Across Global FLUXNET Sites with Regression Algorithms.
Biogeosciences. 13 (14) : pp. 4291-4313. 2016.
[bibtex] [web] [doi] [abstract]
Sven Sickert, Erik Rodner, Joachim Denzler:
Semantic Volume Segmentation with Iterative Context Integration for Bio-medical Image Stacks.
Pattern Recognition and Image Analysis. Advances in Mathematical Theory and Applications (PRIA). 26 (1) : pp. 197-204. 2016.
[bibtex] [pdf] [abstract]
2015
Clemens-Alexander Brust, Sven Sickert, Marcel Simon, Erik Rodner, Joachim Denzler:
Convolutional Patch Networks with Spatial Prior for Road Detection and Urban Scene Understanding.
International Conference on Computer Vision Theory and Applications (VISAPP). Pages 510-517. 2015.
[bibtex] [pdf] [doi] [abstract]
Clemens-Alexander Brust, Sven Sickert, Marcel Simon, Erik Rodner, Joachim Denzler:
Efficient Convolutional Patch Networks for Scene Understanding.
CVPR Workshop on Scene Understanding (CVPR-WS). 2015. Poster presentation and extended abstract
[bibtex] [pdf] [abstract]
2014
Martin Jung, Kazuhito Ichii, Gustau Camps-Valls, Dario Papale, Gianluca Tramontana, Sven Sickert, Christopher Schwalm, Markus Reichstein:
An ensemble of global high-resolution products of energy fluxes over land.
International Scientific Conference on the Global Water and Energy Cycle (GEWEX). 2014. Poster
[bibtex] [abstract]
Sven Sickert, Erik Rodner, Joachim Denzler:
Semantic Volume Segmentation with Iterative Context Integration.
Open German-Russian Workshop on Pattern Recognition and Image Understanding (OGRW). Pages 220-225. 2014.
[bibtex] [pdf] [web] [abstract]