Dr.-Ing. Paul Bodesheim
Paul Bodesheim
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 46410
E-mail:paul (dot) bodesheim (at) uni-jena (dot) de
Room:1218
Links:DBLP, GoogleScholar, LinkedIn, ORCID, publons, ResearchGate, SemanticScholar, XING

Curriculum Vitae

 since Oct 2018
 Research Associate / Postdoc
Computer Vision Group (Prof. Joachim Denzler), Friedrich Schiller University Jena
 Aug 2022 to Sep 2022
 Visiting Academic for two month at the University of Bristol (UK)
Research stay in the group of Tilo Burghardt, Department of Computer Science
 Jun 2020 to Dec 2022
 Team Leader: “Computer Vision and Machine Learning”
Computer Vision Group (Prof. Joachim Denzler), Friedrich Schiller University Jena
 Jan 2015 to Sep 2018
 Research Associate / Postdoc
Department Biogeochemical Integration (Prof. Markus Reichstein), Max Planck Institute for Biogeochemistry
 Apr 2011 to Dec 2014
 Research Associate / PhD Student
Computer Vision Group (Prof. Joachim Denzler), Friedrich Schiller University Jena
PhD Thesis: “Discovering unknown visual objects with novelty detection techniques”
 Oct 2006 to Mar 2011
 Studies in Computer Science (Diploma)
Friedrich Schiller University Jena
Focus: Digitial Image Processing / Computer Vision
Diploma Thesis: “Object Discovery – Unsupervised Learning of Object Categories”

Awards

  • Best Paper Award at Anomaly Detection Workshop of ICML 2016
    (Rodner, Barz, Guanche, Flach, Mahecha, Bodesheim, Reichstein, Denzler: “Maximally Divergent Intervals for Anomaly Detection”)
  • Best Poster Award at FEAST Workshop of ICPR 2014
    (Freytag, Rühle, Bodesheim, Rodner, Denzler: “Seeing through bag-of-visual-word glasses: towards understanding quantization effects in feature extraction methods”)
  • Best Paper Honorable Mention Award at ACCV 2012
    (Freytag, Rodner, Bodesheim, Denzler: “Rapid Uncertainty Computation with Gaussian Processes and Histogram Intersection Kernels”)

Research Interests

  • Visual Object Recognition
  • Learning from Small and Imbalanced Data
  • Fine-grained Recognition and Applications in Biodiversity Research
  • Novelty Detection and Open Set Recognition
  • Active Learning and Lifelong Learning

Projects (Third-Party Funds)

Ongoing
Former

Projects (Further)

Ongoing
Former

Reviewer Activities

Teaching

Winter Terms
Summer Terms
Supervised Theses
  • Felix Kleinsteuber: “Anomaly Detection in Camera Trap Images”. Bachelor Thesis, 2022. (joint supervision with Daphne Auer)
  • Philip Fürste: “Detection of Wildlife in Camera Trap Images using Transformers”. Master Thesis, 2022. (joint supervision with Gideon Stein)
  • Eric Tröbs: “Klassenhierarchien im lebenslangen Lernen” (“Class Hierarchies in Lifelong Learning”). Master Thesis, 2021. (joint supervision with Clemens-Alexander Brust and Dimitri Korsch)
  • Jan Blunk: “Object Tracking in Wildlife Identification”. Bachelor Thesis, 2021. (joint supervision with Matthias Körschens)
  • Daphne Auer: “Applying Wavelet Transforms prior to Convolutional Neural Networks for Image Categorization”. Bachelor Thesis, 2020.
  • Hendrik Happe: “Aktivierungsfunktionen in neuronalen Netzen für die visuelle Objekterkennung” (“Activation Functions in Neural Networks for Visual Object Recognition”). Master Thesis, 2020. (joint supervision with Christian Reimers)
  • Frank Prüfer: “Detektion von unbekannten Objekten durch Entscheidungswälder und Gauß-Prozesse” (“Detecting Unknown Objects with Decision Forests and Gaussian Processes”). Diploma Thesis, 2013.
  • Sven Sickert: “Strategien des Aktiven Lernens” (“Strategies in Active Learning”). Diploma Thesis, 2012. (joint supervision with Alexander Freytag)
Publications
2024
Matthias Körschens, Solveig Franziska Bucher, Paul Bodesheim, Josephine Ulrich, Joachim Denzler, Christine Römermann:
Determining the Community Composition of Herbaceous Species from Images using Convolutional Neural Networks.
Ecological Informatics. pp. 102516. 2024. (in press)
[bibtex] [web] [doi] [abstract]
2023
Jan Blunk, Niklas Penzel, Paul Bodesheim, Joachim Denzler:
Beyond Debiasing: Actively Steering Feature Selection via Loss Regularization.
DAGM German Conference on Pattern Recognition (DAGM-GCPR). 2023.
[bibtex] [pdf] [abstract]
2022
Dimitri Korsch, Paul Bodesheim, Gunnar Brehm, Joachim Denzler:
Automated Visual Monitoring of Nocturnal Insects with Light-based Camera Traps.
CVPR Workshop on Fine-grained Visual Classification (CVPR-WS). 2022.
[bibtex] [pdf] [web] [code] [abstract]
J. Wolfgang Wägele, Paul Bodesheim, Sarah J. Bourlat, Joachim Denzler, Michael Diepenbroek, Vera Fonseca, Karl-Heinz Frommolt, Matthias F. Geiger, Birgit Gemeinholzer, Frank Oliver Glöckner, Timm Haucke, Ameli Kirse, Alexander Kölpin, Ivaylo Kostadinov, Hjalmar S. Kühl, Frank Kurth, Mario Lasseck, Sascha Liedke, Florian Losch, Sandra Müller, Natalia Petrovskaya, Krzysztof Piotrowski, Bernd Radig, Christoph Scherber, Lukas Schoppmann, Jan Schulz, Volker Steinhage, Georg F. Tschan, Wolfgang Vautz, Domenico Velotto, Maximilian Weigend, Stefan Wildermann:
Towards a multisensor station for automated biodiversity monitoring.
Basic and Applied Ecology. 59 : pp. 105-138. 2022.
[bibtex] [web] [doi] [abstract]
Matthias Körschens, Paul Bodesheim, Joachim Denzler:
Beyond Global Average Pooling: Alternative Feature Aggregations for Weakly Supervised Localization.
International Conference on Computer Vision Theory and Applications (VISAPP). Pages 180-191. 2022.
[bibtex] [pdf] [doi] [abstract]
Matthias Körschens, Paul Bodesheim, Joachim Denzler:
Occlusion-Robustness of Convolutional Neural Networks via Inverted Cutout.
International Conference on Pattern Recognition (ICPR). Pages 2829-2835. 2022.
[bibtex] [pdf] [doi] [supplementary] [abstract]
Niklas Penzel, Christian Reimers, Paul Bodesheim, Joachim Denzler:
Investigating Neural Network Training on a Feature Level using Conditional Independence.
ECCV Workshop on Causality in Vision (ECCV-WS). Pages 383-399. 2022.
[bibtex] [pdf] [doi] [abstract]
Paul Bodesheim, Flurin Babst, David C. Frank, Claudia Hartl, Christian S. Zang, Martin Jung, Markus Reichstein, Miguel D. Mahecha:
Predicting spatiotemporal variability in radial tree growth at the continental scale with machine learning.
Environmental Data Science. 1 : pp. E9. 2022.
[bibtex] [doi] [abstract]
Paul Bodesheim, Jan Blunk, Matthias Körschens, Clemens-Alexander Brust, Christoph Käding, Joachim Denzler:
Pre-trained models are not enough: active and lifelong learning is important for long-term visual monitoring of mammals in biodiversity research. Individual identification and attribute prediction with image features from deep neural networks and decoupled decision models applied to elephants and great apes.
Mammalian Biology. 102 : pp. 875-897. 2022.
[bibtex] [web] [doi] [abstract]
Roel van Klink, Tom August, Yves Bas, Paul Bodesheim, Aletta Bonn, Frode Fossoy, Toke T. Hoye, Eelke Jongejans, Myles H.M. Menz, Andreia Miraldo, Tomas Roslin, Helen E. Roy, Ireneusz Ruczynski, Dmitry Schigel, Livia Schäffler, Julie K. Sheard, Cecilie Svenningsen, Georg F. Tschan, Jana Wäldchen, Vera M.A. Zizka, Jens Aström, Diana E. Bowler:
Emerging technologies revolutionise insect ecology and monitoring.
Trends in Ecology \& Evolution. 37 (10) : pp. 872-885. 2022.
[bibtex] [doi] [abstract]
2021
Bernd Radig, Paul Bodesheim, Dimitri Korsch, Joachim Denzler, Timm Haucke, Morris Klasen, Volker Steinhage:
Automated Visual Large Scale Monitoring of Faunal Biodiversity.
Pattern Recognition and Image Analysis. Advances in Mathematical Theory and Applications (PRIA). 31 (3) : pp. 477-488. 2021.
[bibtex] [pdf] [web] [doi] [abstract]
Christian Reimers, Niklas Penzel, Paul Bodesheim, Jakob Runge, Joachim Denzler:
Conditional Dependence Tests Reveal the Usage of ABCD Rule Features and Bias Variables in Automatic Skin Lesion Classification.
CVPR ISIC Skin Image Analysis Workshop (CVPR-WS). Pages 1810-1819. 2021.
[bibtex] [pdf] [web] [abstract]
Christian Reimers, Paul Bodesheim, Jakob Runge, Joachim Denzler:
Conditional Adversarial Debiasing: Towards Learning Unbiased Classifiers from Biased Data.
DAGM German Conference on Pattern Recognition (DAGM-GCPR). Pages 48-62. 2021.
[bibtex] [pdf] [doi] [abstract]
Daphne Auer, Paul Bodesheim, Christian Fiderer, Marco Heurich, Joachim Denzler:
Minimizing the Annotation Effort for Detecting Wildlife in Camera Trap Images with Active Learning.
Computer Science for Biodiversity Workshop (CS4Biodiversity), INFORMATIK 2021. Pages 547-564. 2021.
[bibtex] [pdf] [abstract]
Dimitri Korsch, Paul Bodesheim, Joachim Denzler:
Deep Learning Pipeline for Automated Visual Moth Monitoring: Insect Localization and Species Classification.
INFORMATIK 2021, Computer Science for Biodiversity Workshop (CS4Biodiversity). Pages 443-460. 2021.
[bibtex] [pdf] [web] [doi] [code] [abstract]
Dimitri Korsch, Paul Bodesheim, Joachim Denzler:
End-to-end Learning of Fisher Vector Encodings for Part Features in Fine-grained Recognition.
DAGM German Conference on Pattern Recognition (DAGM-GCPR). Pages 142-158. 2021.
[bibtex] [pdf] [web] [doi] [code] [abstract]
Julia Böhlke, Dimitri Korsch, Paul Bodesheim, Joachim Denzler:
Exploiting Web Images for Moth Species Classification.
Computer Science for Biodiversity Workshop (CS4Biodiversity), INFORMATIK 2021. Pages 481-498. 2021.
[bibtex] [pdf] [web] [doi] [abstract]
Julia Böhlke, Dimitri Korsch, Paul Bodesheim, Joachim Denzler:
Lightweight Filtering of Noisy Web Data: Augmenting Fine-grained Datasets with Selected Internet Images.
International Conference on Computer Vision Theory and Applications (VISAPP). Pages 466-477. 2021.
[bibtex] [pdf] [web] [doi] [abstract]
Matthias Körschens, Paul Bodesheim, Christine Römermann, Solveig Franziska Bucher, Mirco Migliavacca, Josephine Ulrich, Joachim Denzler:
Automatic Plant Cover Estimation with Convolutional Neural Networks.
Computer Science for Biodiversity Workshop (CS4Biodiversity), INFORMATIK 2021. Pages 499-516. 2021.
[bibtex] [pdf] [doi] [abstract]
Matthias Körschens, Paul Bodesheim, Christine Römermann, Solveig Franziska Bucher, Mirco Migliavacca, Josephine Ulrich, Joachim Denzler:
Weakly Supervised Segmentation Pretraining for Plant Cover Prediction.
DAGM German Conference on Pattern Recognition (DAGM-GCPR). Pages 589-603. 2021.
[bibtex] [pdf] [doi] [supplementary] [abstract]
2020
Martin Jung, Christopher Schwalm, Mirco Migliavacca, Sophia Walther, Gustau Camps-Valls, Sujan Koirala, Peter Anthoni, Simon Besnard, Paul Bodesheim, Nuno Carvalhais, Frederic Chevallier, Fabian Gans, Daniel S. Goll, Vanessa Haverd, Philipp Köhler, Kazuhito Ichii, Atul K. Jain, Junzhi Liu, Danica Lombardozzi, Julia E.M.S. Nabel, Jacob A. Nelson, Michael O’Sullivan, Martijn Pallandt, Dario Papale, Wouter Peters, Julia Pongratz, Christian Rödenbeck, Stephen Sitch, Gianluca Tramontana, Anthony Walker, Ulrich Weber, Markus Reichstein:
Scaling carbon fluxes from eddy covariance sites to globe: synthesis and evaluation of the FLUXCOM approach.
Biogeosciences. 17 (5) : pp. 1343-1365. 2020.
[bibtex] [pdf] [web] [doi] [abstract]
Matthias Körschens, Paul Bodesheim, Christine Römermann, Solveig Franziska Bucher, Josephine Ulrich, Joachim Denzler:
Towards Confirmable Automated Plant Cover Determination.
ECCV Workshop on Computer Vision Problems in Plant Phenotyping (CVPPP). 2020.
[bibtex] [pdf] [web] [doi] [supplementary] [abstract]
Miguel D. Mahecha, Fabian Gans, Gunnar Brandt, Rune Christiansen, Sarah E. Cornell, Normann Fomferra, Guido Kraemer, Jonas Peters, Paul Bodesheim, Gustau Camps-Valls, Jonathan F. Donges, Wouter Dorigo, Lina M. Estupinan-Suarez, Victor H. Gutierrez-Velez, Martin Gutwin, Martin Jung, Maria C. Londono, Diego Miralles, Phillip Papastefanou, Markus Reichstein:
Earth system data cubes unravel global multivariate dynamics.
Earth System Dynamics. 11 (1) : pp. 201-234. 2020.
[bibtex] [pdf] [web] [doi] [abstract]
2019
Dimitri Korsch, Paul Bodesheim, Joachim Denzler:
Classification-Specific Parts for Improving Fine-Grained Visual Categorization.
DAGM German Conference on Pattern Recognition (DAGM-GCPR). Pages 62-75. 2019.
[bibtex] [pdf] [web] [doi] [code] [abstract]
2018
Flurin Babst, Paul Bodesheim, Noah Charney, Andrew D. Friend, Martin P. Girardin, Stefan Klesse, David J.P. Moore, Kristina Seftigen, Jesper Björklund, Olivier Bouriaud, Andria Dawson, R. Justin DeRose, Michael C. Dietze, Annemarie H. Eckes, Brian Enquist, David C. Frank, Miguel D. Mahecha, Benjamin Poulter, Sydne Record, Valerie Trouet, Rachael H. Turton, Zhen Zhang, Margaret E.K. Evans:
When tree rings go global: challenges and opportunities for retro-and prospective insight.
Quaternary Science Reviews. 197 : pp. 1-20. 2018.
[bibtex] [pdf] [web] [doi] [abstract]
Gaia Vaglio Laurin, Cristina Vittucci, Gianluca Tramontana, Paul Bodesheim, Paolo Ferrazzoli, Leila Guerriero, Martin Jung, Miguel D. Mahecha, Dario Papale:
SMOS Vegetation Optical Depth and Ecosystem Functional Properties: Exploring Their Relationships in Tropical Forests.
IEEE International Geoscience and Remote Sensing Symposium (IGARSS). Pages 5891-5894. 2018.
[bibtex] [pdf] [web] [doi] [abstract]
Paul Bodesheim:
Discovering unknown visual objects with novelty detection techniques.
2018. Dissertation. ISBN: 978-3-8439-3546-3
[bibtex] [web] [abstract]
Paul Bodesheim, Martin Jung, Fabian Gans, Miguel D. Mahecha, Markus Reichstein:
Upscaled diurnal cycles of land-atmosphere fluxes: a new global half-hourly data product.
Earth System Science Data. 10 (3) : pp. 1327-1365. 2018.
[bibtex] [pdf] [web] [doi] [abstract]
2017
Erik Rodner, Alexander Freytag, Paul Bodesheim, Björn Fröhlich, Joachim Denzler:
Large-Scale Gaussian Process Inference with Generalized Histogram Intersection Kernels for Visual Recognition Tasks.
International Journal of Computer Vision (IJCV). 121 (2) : pp. 253-280. 2017.
[bibtex] [pdf] [web] [doi] [abstract]
Flurin Babst, Benjamin Poulter, Paul Bodesheim, Miguel D. Mahecha, David C. Frank:
Improved tree-ring archives will support earth-system science.
Nature Ecology \& Evolution. 1 (2) : 2017.
[bibtex] [pdf] [web] [doi] [abstract]
Flurin Babst, Olivier Bouriaud, Benjamin Poulter, Zhen Zhang, Valerie Trouet, Margaret Evans, Noah Charney, Sydne Record, Brian Enquist, Kristina Seftigen, Jesper Björklund, Stefan Klesse, Paul Bodesheim, Miguel Mahecha, Martin Girardin, Andrew Friend, David Frank:
When tree rings go global: challenges and opportunities for retro- andprospective insights.
European Geosciences Union General Assembly (EGU): Abstract + Oral Presentation. 2017.
[bibtex] [pdf] [web] [abstract]
Milan Flach, Fabian Gans, Alexander Brenning, Joachim Denzler, Markus Reichstein, Erik Rodner, Sebastian Bathiany, Paul Bodesheim, Yanira Guanche, Sebasitan Sippel, Miguel D. Mahecha:
Multivariate anomaly detection for Earth observations: a comparison of algorithms and feature extraction techniques.
Earth System Dynamics. 8 (3) : pp. 677-696. 2017.
[bibtex] [pdf] [web] [doi] [abstract]
Paul Bodesheim, Martin Jung, Miguel D. Mahecha, Markus Reichstein:
Upscaling diurnal cycles of carbon fluxes.
European Geosciences Union General Assembly (EGU): Abstract + Poster Presentation. 2017.
[bibtex] [pdf] [web] [abstract]
2016
Erik Rodner, Björn Barz, Yanira Guanche, Milan Flach, Miguel Mahecha, Paul Bodesheim, Markus Reichstein, Joachim Denzler:
Maximally Divergent Intervals for Anomaly Detection.
Workshop on Anomaly Detection (ICML-WS). 2016. Best Paper Award
[bibtex] [pdf] [web] [code] [abstract]
Markus Reichstein, Martin Jung, Paul Bodesheim, Miguel D. Mahecha, Fabian Gans, Erik Rodner, Gustau Camps-Valls, Dario Papale, Gianluca Tramontana, Joachim Denzler, Dennis D. Baldocchi:
Potential of new machine learning methods for understanding long-term interannual variability of carbon and energy fluxes and states from site to global scale.
American Geophysical Union Fall Meeting (AGU): Abstract + Oral Presentation. 2016.
[bibtex] [web] [abstract]
Milan Flach, Miguel Mahecha, Fabian Gans, Erik Rodner, Paul Bodesheim, Yanira Guanche-Garcia, Alexander Brenning, Joachim Denzler, Markus Reichstein:
Using Statistical Process Control for detecting anomalies in multivariate spatiotemporal Earth Observations.
European Geosciences Union General Assembly (EGU): Abstract + Oral Presentation. 2016.
[bibtex] [pdf] [web] [abstract]
Milan Flach, Sebastian Sippel, Paul Bodesheim, Alexander Brenning, Joachim Denzler, Fabian Gans, Yanira Guanche, Markus Reichstein, Erik Rodner, Miguel D. Mahecha:
Hot spots of multivariate extreme anomalies in Earth observations.
American Geophysical Union Fall Meeting (AGU): Abstract + Oral Presentation. 2016.
[bibtex] [web] [abstract]
Sebastian Sippel, Holger Lange, Miguel D. Mahecha, Michael Hauhs, Paul Bodesheim, Thomas Kaminski, Fabian Gans, Osvaldo A. Rosso:
Diagnosing the Dynamics of Observed and Simulated Ecosystem Gross Primary Productivity with Time Causal Information Theory Quantifiers.
PLOS ONE. 11 (10) : pp. 1-29. 2016.
[bibtex] [pdf] [web] [doi] [abstract]
2015
Christoph Käding, Alexander Freytag, Erik Rodner, Paul Bodesheim, Joachim Denzler:
Active Learning and Discovery of Object Categories in the Presence of Unnameable Instances.
IEEE Conference on Computer Vision and Pattern Recognition (CVPR). Pages 4343-4352. 2015.
[bibtex] [pdf] [web] [doi] [code] [presentation] [supplementary] [abstract]
Gustau Camps-Valls, Martin Jung, Kazuhito Ichii, Dario Papale, Gianluca Tramontana, Paul Bodesheim, Christopher Schwalm, Jakob Zscheischler, Miguel D. Mahecha, Markus Reichstein:
Ranking drivers of global carbon and energy fluxes over land.
IEEE International Geoscience and Remote Sensing Symposium (IGARSS). Pages 4416-4419. 2015.
[bibtex] [pdf] [web] [doi] [abstract]
Paul Bodesheim, Alexander Freytag, Erik Rodner, Joachim Denzler:
Local Novelty Detection in Multi-class Recognition Problems.
IEEE Winter Conference on Applications of Computer Vision (WACV). Pages 813-820. 2015.
[bibtex] [pdf] [web] [doi] [supplementary] [abstract]
2014
Alexander Freytag, Johannes Rühle, Paul Bodesheim, Erik Rodner, Joachim Denzler:
Seeing through bag-of-visual-word glasses: towards understanding quantization effects in feature extraction methods.
ICPR Workshop on Features and Structures (FEAST): Extended Abstract + Poster Presentation. 2014. Best Poster Award
[bibtex] [pdf] [code] [presentation]
Alexander Freytag, Johannes Rühle, Paul Bodesheim, Erik Rodner, Joachim Denzler:
Seeing through bag-of-visual-word glasses: towards understanding quantization effects in feature extraction methods.
2014. Technical Report TR-FSU-INF-CV-2014-01
[bibtex] [pdf] [code] [abstract]
Mahesh Venkata Krishna, Paul Bodesheim, Marco Körner, Joachim Denzler:
Temporal Video Segmentation by Event Detection: A Novelty Detection Approach.
Pattern Recognition and Image Analysis. Advances in Mathematical Theory and Applications (PRIA). 24 (2) : pp. 243-255. 2014.
[bibtex] [pdf] [web] [doi] [abstract]
2013
Alexander Freytag, Erik Rodner, Paul Bodesheim, Joachim Denzler:
Labeling examples that matter: Relevance-Based Active Learning with Gaussian Processes.
DAGM German Conference on Pattern Recognition (DAGM-GCPR). Pages 282-291. 2013.
[bibtex] [pdf] [web] [doi] [code] [supplementary] [abstract]
Joachim Denzler, Erik Rodner, Paul Bodesheim, Alexander Freytag:
Beyond the closed-world assumption: The importance of novelty detection and open set recognition.
GCPR/DAGM Workshop on Unsolved Problems in Pattern Recognition and Computer Vision (GCPR-WS): Extended Abstract + Oral Presentation. 2013.
[bibtex] [pdf] [web]
Mahesh Venkata Krishna, Paul Bodesheim, Joachim Denzler:
Video Segmentation by Event Detection: A Novel One-class Classification Approach.
4th International Workshop on Image Mining. Theory and Applications (IMTA-4). 2013.
[bibtex] [pdf] [abstract]
Paul Bodesheim, Alexander Freytag, Erik Rodner, Joachim Denzler:
An Efficient Approximation for Gaussian Process Regression.
2013. Technical Report TR-FSU-INF-CV-2013-01
[bibtex] [pdf]
Paul Bodesheim, Alexander Freytag, Erik Rodner, Joachim Denzler:
Approximations of Gaussian Process Uncertainties for Visual Recognition Problems.
Scandinavian Conference on Image Analysis (SCIA). Pages 182-194. 2013.
[bibtex] [pdf] [web] [doi] [abstract]
Paul Bodesheim, Alexander Freytag, Erik Rodner, Michael Kemmler, Joachim Denzler:
Kernel Null Space Methods for Novelty Detection.
IEEE Conference on Computer Vision and Pattern Recognition (CVPR). Pages 3374-3381. 2013.
[bibtex] [pdf] [web] [doi] [code] [presentation] [abstract]
2012
Alexander Freytag, Erik Rodner, Paul Bodesheim, Joachim Denzler:
Beyond Classification - Large-scale Gaussian Process Inference and Uncertainty Prediction.
Big Data Meets Computer Vision: First International Workshop on Large Scale Visual Recognition and Retrieval (NIPS-WS). 2012. This workshop article is a short version of our ACCV 2012 paper.
[bibtex] [pdf] [abstract]
Alexander Freytag, Erik Rodner, Paul Bodesheim, Joachim Denzler:
Rapid Uncertainty Computation with Gaussian Processes and Histogram Intersection Kernels.
Asian Conference on Computer Vision (ACCV). Pages 511-524. 2012. Best Paper Honorable Mention Award
[bibtex] [pdf] [web] [doi] [presentation] [abstract]
Erik Rodner, Alexander Freytag, Paul Bodesheim, Joachim Denzler:
Large-Scale Gaussian Process Classification with Flexible Adaptive Histogram Kernels.
European Conference on Computer Vision (ECCV). Pages 85-98. 2012.
[bibtex] [pdf] [web] [doi] [supplementary] [abstract]
Paul Bodesheim, Erik Rodner, Alexander Freytag, Joachim Denzler:
Divergence-Based One-Class Classification Using Gaussian Processes.
British Machine Vision Conference (BMVC). Pages 50.1-50.11. 2012.
[bibtex] [pdf] [web] [doi] [presentation] [abstract]
2011
Paul Bodesheim:
Spectral Clustering of ROIs for Object Discovery.
Symposium of the German Association for Pattern Recognition (DAGM). Pages 450-455. 2011.
[bibtex] [pdf] [web] [doi] [abstract]