Institut für Informationsverarbeitung (TNT)

Florian Kluger studied Electrical Engineering and Information Technology at Leibniz Universität Hannover, and graduated with an MSc in September 2017. As part of his Bachelor's studies, he attended Yonsei University in Seoul, South Korea, in the summer of 2014. For his Master's thesis – "Automated Extraction of Geometric Scene Features" – he received the advancement award of the NiedersachsenMetall foundation. During the summer of 2017, he interned at Sony R&D in Tokyo, Japan, where he conducted research on lossy representations of 3D point cloud data.

Since October 2017, he pursues a PhD at the Institut für Informationsverarbeitung at Leibniz Universität Hannover. His main research interests are Machine Learning and its applications in Computer Vision.

Personal Website • Google Scholar • github

Awards

Other Activities

In his spare time, Florian is an avid cyclist and hobbyist photographer: flickr • Strava

Publications

Show recent publications only

Conference Contributions
- Florian Kluger, Bodo Rosenhahn
  PARSAC: Accelerating Robust Multi-Model Fitting with Parallel Sample Consensus
  AAAI, February 2024
  (Arxiv.org) BibTeX
- Martin Knura, Florian Kluger, Moris Zahtila, Jochen Schiewe, Bodo Rosenhahn, Dirk Burghardt
  Using Object Detection on Social Media Images for Urban Bicycle Infrastructure Planning: A Case Study of Dresden
  ISPRS International Journal of Geo-Information, October 2021
  (DOI) BibTeX
- Florian Kluger, Hanno Ackermann, Eric Brachmann, Michael Ying Yang, Bodo Rosenhahn
  Cuboids Revisited: Learning Robust 3D Shape Fitting to Single RGB Images
  CVPR, June 2021
  (Arxiv.org) BibTeX
- Florian Kluger, Hanno Ackermann, Michael Ying Yang, Bodo Rosenhahn
  Temporally Consistent Horizon Lines
  International Conference on Robotics and Automation (ICRA), Paris, France, June 2020
  (Arxiv.org) BibTeX
- Florian Kluger, Eric Brachmann, Hanno Ackermann, Carsten Rother, Michael Ying Yang, Bodo Rosenhahn
  CONSAC: Robust Multi-Model Fitting by Conditional Sample Consensus
  Computer Vision and Pattern Recognition (CVPR), Seattle, WA, USA, June 2020
  (Arxiv.org) 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
- Florian Kluger, Hanno Ackermann, Michael Ying Yang, Bodo Rosenhahn
  Deep Learning for Vanishing Point Detection Using an Inverse Gnomonic Projection
  39th German Conference on Pattern Recognition, Springer Lecture Notes in Computer Science (LNCS), Basel, Switzerland, September 2017
  (pdfDOI) BibTeX
- Holger Meuel, Stephan Ferenz, Florian Kluger, Jörn Ostermann
  Robust Long-Term Aerial Video Mosaicking by Weighted Feature-based Global Motion Estimation
  17th International Conference on Computer Analysis of Images and Patterns (CAIP), Ystad, Sweden, Proceedings, Part I, Springer International Publishing, Vol. 1, pp. 135-147, Cham, August 2017, edited by Felsberg, Michael and Heyden, Anders and Krüger, Norbert
  (pdf, pdf, pdfDOI) BibTeX
- Holger Meuel, Marco Munderloh, Florian Kluger, Jörn Ostermann
  Codec Independent Region of Interest Video Coding using a Joint Pre- and Postprocessing Framework
  Proc. of the IEEE International Conference on Multimedia and Expo (ICME), pp. 1-6, Seattle, Washington, USA, July 2016
  (pdf, pdf) BibTeX
- Holger Meuel, Florian Kluger, Jörn Ostermann
  Illumination Change Robust, Codec Independent Low Bit Rate Coding of Stereo from Singleview Aerial Video
  Proc. of the 10th IEEE 3DTV Conference (3DTV-CON), pp. 1-4, Hamburg, Germany, July 2016
  (pdfIEEEexplore) BibTeX
Journals
- Florian Kluger, Eric Brachmann, Michael Ying Yang, Bodo Rosenhahn
  Robust Shape Fitting for 3D Scene Abstraction
  IEEE Transactions on Pattern Analysis and Machine Intelligence, March 2024
  (Arxiv.org) BibTeX
Technical Report
- Holger Meuel, Florian Kluger, Jörn Ostermann
  Region of Interest Coding for Aerial Surveillance Video Using AVC & HEVC
  arXiv Technical Report, Institut für Informationsverarbeitung, October 2015
  (pdfArxiv.org) BibTeX