Dr. rer. nat. Björn Barz
Curriculum Vitae
since 2021 Machine Learning Scientist
Carl Zeiss AG
Corporate Research & Technology
2020-2021 PostDoc Researcher
Friedrich Schiller University Jena, Computer Vision Group
Research focus: Integration of prior knowledge
2016-2020 PhD Student
Friedrich Schiller University Jena, Computer Vision Group
PhD Thesis: “Semantic and Interactive Content-based Image Retrieval”
2014-2016 M.Sc. in Computer Science
Friedrich Schiller University Jena
Master’s Thesis: “Detection of Anomalous Intervals in Multivariate Spatio-Temporal Time-Series”
2011-2014 B.Sc. in Computer Science
Friedrich Schiller University Jena
Bachelor’s Thesis: “Interactive Learning of Object Detectors”
Research Interests
  • Deep Learning
  • Image Retrieval
  • Metric Learning
  • Active Learning
  • Object Detection
  • Natural Language Processing
Projects
Further Activities
Publications
2022
Björn Barz, Joachim Denzler:
Weakly-Supervised Localization of Multiple Objects in Images using Cosine Loss.
International Conference on Computer Vision Theory and Applications (VISAPP). Pages 287-296. 2022.
[bibtex] [doi] [abstract]
Lorenzo Brigato, Björn Barz, Luca Iocchi, Joachim Denzler:
Image Classification with Small Datasets: Overview and Benchmark.
IEEE Access. 10 : pp. 49233-49250. 2022.
[bibtex] [pdf] [web] [doi] [abstract]
2021
Bernd Gruner, Matthias Körschens, Björn Barz, Joachim Denzler:
Domain Adaptation and Active Learning for Fine-Grained Recognition in the Field of Biodiversity.
Findings of the CVPR Workshop on Continual Learning in Computer Vision (CLVision). 2021.
[bibtex] [abstract]
Björn Barz, Joachim Denzler:
Content-based Image Retrieval and the Semantic Gap in the Deep Learning Era.
ICPR Workshop on Content-Based Image Retrieval (CBIR2020). Pages 245-260. 2021.
[bibtex] [pdf] [doi] [abstract]
Björn Barz, Joachim Denzler:
WikiChurches: A Fine-Grained Dataset of Architectural Styles with Real-World Challenges.
NeurIPS 2021 Track on Datasets and Benchmarks. 2021.
[bibtex] [pdf] [presentation] [abstract]
Björn Barz, Kai Schröter, Ann-Christin Kra, Joachim Denzler:
Finding Relevant Flood Images on Twitter using Content-based Filters.
ICPR Workshop on Machine Learning Advances Environmental Science (MAES). Pages 5-14. 2021.
[bibtex] [pdf] [web] [doi] [abstract]
Clemens-Alexander Brust, Björn Barz, Joachim Denzler:
Carpe Diem: A Lifelong Learning Tool for Automated Wildlife Surveillance.
Computer Science for Biodiversity Workshop (CS4Biodiversity), INFORMATIK 2021. Pages 417-423. 2021.
[bibtex] [pdf] [doi]
Clemens-Alexander Brust, Björn Barz, Joachim Denzler:
Self-Supervised Learning from Semantically Imprecise Data.
arXiv preprint arXiv:2104.10901. 2021.
[bibtex] [pdf] [abstract]
Felix Schneider, Björn Barz, Joachim Denzler:
Detecting Scenes in Fiction Using the Embedding Delta Signal.
KONVENS Shared Task on Scene Segmentation. 2021.
[bibtex]
Felix Schneider, Phillip Brandes, Björn Barz, Sophie Marshall, Joachim Denzler:
Data-Driven Detection of General Chiasmi Using Lexical and Semantic Features.
SIGHUM Workshop on Computational Linguistics for Cultural Heritage, Social Sciences, Humanities and Literature. Pages 96-100. 2021.
[bibtex] [web] [doi] [abstract]
Lorenzo Brigato, Björn Barz, Luca Iocchi, Joachim Denzler:
Tune It or Don't Use It: Benchmarking Data-Efficient Image Classification.
ICCV Workshop on Visual Inductive Priors for Data-Efficient Deep Learning. 2021.
[bibtex] [pdf] [abstract]
Violeta Teodora Trifunov, Maha Shadaydeh, Björn Barz, Joachim Denzler:
Anomaly Attribution of Multivariate Time Series using Counterfactual Reasoning.
IEEE International Conference on Machine Learning and Applications (ICMLA). Pages 166-172. 2021.
[bibtex] [pdf] [web] [doi] [abstract]
2020
Björn Barz:
Semantic and Interactive Content-based Image Retrieval.
2020. Dissertation. ISBN 978-3-7369-7346-6.
[bibtex] [web]
Björn Barz, Joachim Denzler:
Deep Learning on Small Datasets without Pre-Training using Cosine Loss.
IEEE Winter Conference on Applications of Computer Vision (WACV). Pages 1360-1369. 2020.
[bibtex] [pdf] [doi] [code] [abstract]
Björn Barz, Joachim Denzler:
Do We Train on Test Data? Purging CIFAR of Near-Duplicates.
Journal of Imaging. 6 (6) : 2020.
[bibtex] [pdf] [web] [doi] [abstract]
Clemens-Alexander Brust, Björn Barz, Joachim Denzler:
Making Every Label Count: Handling Semantic Imprecision by Integrating Domain Knowledge.
International Conference on Pattern Recognition (ICPR). 2020.
[bibtex] [pdf] [doi] [abstract]
2019
Björn Barz, Christoph Käding, Joachim Denzler:
Information-Theoretic Active Learning for Content-Based Image Retrieval.
DAGM German Conference on Pattern Recognition (DAGM-GCPR). Pages 650-666. 2019.
[bibtex] [pdf] [doi] [code] [supplementary] [abstract]
Björn Barz, Erik Rodner, Yanira Guanche Garcia, Joachim Denzler:
Detecting Regions of Maximal Divergence for Spatio-Temporal Anomaly Detection.
IEEE Transactions on Pattern Analysis and Machine Intelligence. 41 (5) : pp. 1088-1101. 2019. (Pre-print published in 2018.)
[bibtex] [pdf] [web] [doi] [code] [abstract]
Björn Barz, Joachim Denzler:
Hierarchy-based Image Embeddings for Semantic Image Retrieval.
IEEE Winter Conference on Applications of Computer Vision (WACV). Pages 638-647. 2019. Best Paper Award
[bibtex] [pdf] [web] [doi] [code] [presentation] [supplementary] [abstract]
Björn Barz, Prerana Mukherjee, Brejesh Lall, Elham Vahdati:
Diverse Perspectives on the Relationship between Artificial Intelligence and Pattern Recognition.
Frontiers in Pattern Recognition and Artificial Intelligence. Pages 23-34. 2019.
[bibtex] [web] [doi] [abstract]
2018
Björn Barz:
On the Relation Between Artifical Intelligence and Pattern Recognition.
ICPRAI 2018 Competition. 2018. Award-winning Entry
[bibtex] [pdf]
Björn Barz, Joachim Denzler:
Automatic Query Image Disambiguation for Content-Based Image Retrieval.
International Conference on Computer Vision Theory and Applications (VISAPP). Pages 249-256. 2018.
[bibtex] [pdf] [doi] [code] [abstract]
Björn Barz, Joachim Denzler:
Deep Learning is not a Matter of Depth but of Good Training.
International Conference on Pattern Recognition and Artificial Intelligence (ICPRAI). Pages 683-687. 2018.
[bibtex] [pdf] [abstract]
Björn Barz, Kai Schröter, Moritz Münch, Bin Yang, Andrea Unger, Doris Dransch, Joachim Denzler:
Enhancing Flood Impact Analysis using Interactive Retrieval of Social Media Images.
Archives of Data Science, Series A. 5 (1) : pp. A06, 21 S. online. 2018.
[bibtex] [pdf] [doi] [abstract]
Björn Barz, Thomas C. van Dijk, Bert Spaan, Joachim Denzler:
Putting User Reputation on the Map: Unsupervised Quality Control for Crowdsourced Historical Data.
2nd ACM SIGSPATIAL Workshop on Geospatial Humanities. Pages 3:1-3:6. 2018.
[bibtex] [pdf] [doi] [abstract]
Christoph Käding, Erik Rodner, Alexander Freytag, Oliver Mothes, Björn Barz, Joachim Denzler:
Active Learning for Regression Tasks with Expected Model Output Changes.
British Machine Vision Conference (BMVC). 2018.
[bibtex] [pdf] [supplementary] [abstract]
Matthias Körschens, Björn Barz, Joachim Denzler:
Towards Automatic Identification of Elephants in the Wild.
AI for Wildlife Conservation Workshop (AIWC). 2018.
[bibtex] [pdf] [abstract]
2017
Björn Barz, Erik Rodner, Christoph Käding, Joachim Denzler:
Fast Learning and Prediction for Object Detection using Whitened CNN Features.
arXiv preprint arXiv:1704.02930. 2017.
[bibtex] [pdf] [web]
Björn Barz, Yanira Guanche, Erik Rodner, Joachim Denzler:
Maximally Divergent Intervals for Extreme Weather Event Detection.
MTS/IEEE OCEANS Conference Aberdeen. Pages 1-9. 2017.
[bibtex] [pdf] [doi] [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]
2014
Björn Barz, Erik Rodner, Joachim Denzler:
ARTOS -- Adaptive Real-Time Object Detection System.
arXiv preprint arXiv:1407.2721. 2014.
[bibtex] [pdf] [web] [code] [abstract]