Daniel Kienzle
Telefon: | +49 (821) 598 2451 |
E-Mail: | daniel.kienzle@uni-auni-a.de () |
Raum: | 1018 (N) |
Sprechzeiten: | Nach Vereinbarung |
Adresse: | Universitätsstraße 6a, 86159 Augsburg |
Lebenslauf
- Physics in Machine Learning
- Object Localization
- Pose Estimation
- Self-supervised learning
Publikationen
2024 |
Julian Lorenz, Alexander Pest, Daniel Kienzle, Katja Ludwig and Rainer Lienhart. 2024. A fair ranking and new model for panoptic scene graph generation. In Aleš Leonardis, Elisa Ricci, Stefan Roth, Olga Russakovsky, Torsten Sattler, Gül Varol (Eds.). Computer Vision – ECCV 2024: 18th European Conference, Milan, Italy, September 29 – October 4, 2024, proceedings, part LXI. Springer, Berlin, 148-164 DOI: 10.1007/978-3-031-73030-6_9 |
Daniel Kienzle, Marco Kantonis, Robin Schön and Rainer Lienhart. in press. Segformer++: efficient token-merging strategies for high-resolution semantic segmentation. In IEEE International Conference on Multimedia Information Processing and Retrieval (MIPR) 2024, San Jose, CA, USA, August 7-9, 2024. IEEE, Piscataway, NJ |
Luuk H. Boulogne, Julian Lorenz, Daniel Kienzle, Robin Schön, Katja Ludwig, Rainer Lienhart, Simon Jegou, Guang Li, Cong Chen, Qi Wang, Derik Shi, Mayug Maniparambil, Dominik Müller, Silvan Mertes, Niklas Schröter, Fabio Hellmann, Miriam Elia, Ine Dirks, Matias Nicolas Bossa, Abel Diaz Berenguer, Tanmoy Mukherjee, Jef Vandemeulebroucke, Hichem Sahli, Nikos Deligiannis, Panagiotis Gonidakis, Ngoc Dung Huynh, Imran Razzak, Reda Bouadjenek, Mario Verdicchio, Pasquale Borrelli, Marco Aiello, James A. Meakin, Alexander Lemm, Christoph Russ, Razvan Ionasec, Nikos Paragios, Bram van Ginneken and Marie-Pierre Revel Dubios. 2024. The STOIC2021 COVID-19 AI challenge: applying reusable training methodologies to private data. Medical Image Analysis 97, 103230. DOI: 10.1016/j.media.2024.103230 |
Daniel Kienzle, Katja Ludwig, Julian Lorenz and Rainer Lienhart. 2024. Towards learning monocular 3D object localization from 2D labels using the physical laws of motion. In Theodora Kontogianni, Akihiro Sugimoto, Gopal Sharma (Eds.). International Conference on 3D Vision 2024 (3DV), March 18-21, 2024, Davos, Switzerland. IEEE, Piscataway, NJ, 1564-1573 DOI: 10.1109/3DV62453.2024.00155 |
Robin Schön, Daniel Kienzle and Rainer Lienhart. in press. WSESeg: introducing a dataset for the segmentation of winter sports equipment with a baseline for interactive segmentation. In 21st International Conference on Content-based Multimedia Indexing, September 18-20, 2024, Reykjavik, Iceland. IEEE, Piscataway, NJ |
2023 |
Daniel Kienzle, Julian Lorenz, Robin Schön, Katja Ludwig and Rainer Lienhart. 2023. COVID detection and severity prediction with 3D-ConvNeXt and custom pretrainings. In Leonid Karlinsky, Tomer Michaeli, Ko Nishino (Eds.). Computer Vision – ECCV 2022 Workshops: Tel Aviv, Israel, October 23–27, 2022, Proceedings, Part VII. Springer, Berlin, 500-516 DOI: 10.1007/978-3-031-25082-8_33 |
Katja Ludwig, Daniel Kienzle, Julian Lorenz and Rainer Lienhart. 2023. Detecting arbitrary keypoints on limbs and skis with sparse partly correct segmentation masks. In IEEE/CVF Winter Conference on Applications of Computer Vision Workshops (WACVW), Jan. 3 2023 to Jan. 7 2023, Waikoloa, HI, USA. IEEE, Piscataway, NJ, 1-10 DOI: 10.1109/WACVW58289.2023.00051 |
Julian Lorenz, Florian Barthel, Daniel Kienzle and Rainer Lienhart. 2023. Haystack: a panoptic scene graph dataset to evaluate rare predicate classes. In 2023 IEEE International Conference on Computer Vision Workshops (ICCVW), October 2-6, 2023, Paris, France. IEEE, Piscataway, NJ, 62-70 DOI: 10.1109/ICCVW60793.2023.00013 |
2022 |
Katja Ludwig, Daniel Kienzle and Rainer Lienhart. 2022. Recognition of freely selected keypoints on human limbs. In Rama Chellappa, Jiri Matas, Long Quan, Mubarak Shah, Eric Mortensen (Eds.). 2022 IEEE/CVF International Conference on Computer Vision and Pattern Recognition Workshops (CVPRW), New Orleans, LA, USA, 19-24 June 2022. IEEE, Piscataway, NJ, 3530-3538 DOI: 10.1109/CVPRW56347.2022.00397 |
Betreute Abschlussarbeiten
- Gregor Böhm, Uncertainity for 3D Ball Localization, Projektmodul, September 2024
- Felix Lettowsky, Comparison of Different Methods for 3D Ball Localization on Various Datasets, Masterarbeit, September 2024
- Norman Szabo, Segmentation Using Attention Masks, Projektmodul, August 2024
- Marco Kantonis, Analysis of Token-Merging Techniques for Transformer-Based Semantic Segmentation, Masterarbeit, Mai 2024
- Lukas Bayer, Incorporating Token Merging Into Transformers for Efficient Ground State Search of Quantum Spin Models Using minSR, Bachelorarbeit, Mai 2024
- Simon Reichert, Exploring Image Registration Techniques for XANES Data using Traditional Methods and Machine Learning Techniques, Bachelorarbeit, April 2024
- Felix Lettowsky, Verwendung der Brax-Engine zum Erlernen dreidimensionaler Objektlokalisierung, Projektmodul, März 2024
- Clarissa Dinu-Fröhlich, Erstellung von Modellen zur Semantischen Segmentierung von Körperteilen unter Verwendung von schwachen Segementierungsmasken, Projektmodul, Juni 2023
- Jan Claar, Measurement of Droplets in Vaporized Fluids using Machine Learning Techniques, Bachelorarbeit, März 2023
- Jonas Kell, Investigation of transformer architectures for geometrical graph structures and their application to two-dimensional spin systems, Bachelorarbeit, Oktober 2022
- Dennis Knof, Generating artificial datasets with MuJoCo, Betriebspraktikum, August 2022
- Patrick Hopf, Zeitliche Dynamik in Quantenbillards mit Hilfe neuronaler Netze, Bachelorarbeit, Dezember 2021
Lehre
- WS 2021/22: Grundlagen der Signalverarbeitung und des Maschinellen Lernens
- SS 2022: Machine Learning and Computer Vision
- WS 2022/23: Grundlagen der Signalverarbeitung und des Maschinellen Lernens
- SS 2023: Machine Learning and Computer Vision, Seminar über Multimedia und Maschinelles Sehen, Seminar über Multimediale Datenverarbeitung
- WS 2023/24: Grundlagen der Signalverarbeitung und des Maschinellen Lernens, Seminar über Multimedia und Maschinelles Sehen, Seminar über Multimediale Datenverarbeitung
- SS 2024: Machine Learning and Computer Vision, Seminar über Multimedia und Maschinelles Sehen, Seminar über Multimediale Datenverarbeitung