Chair for Machine Learning & Computer Vision

  1. University
  2. Faculties
  3. Faculty of Applied Computer Science
  4. Institute of Computer Science
  5. Chairs and Professors
  6. Machine Learning & Computer Vision
  7. Team
  8. Daniel Kienzle

Daniel Kienzle

Research Assistant & PhD Student
Chair for Machine Learning & Computer Vision
Phone: +49 (821) 598 4386
Email:
Room: 1025 ( N )
Open hours: by appointment
Address: Universitätsstraße 6a, 86159 Augsburg

CV

Education:
2021 - Now    PhD in Machine Learning and Computer Vision at the University of Augsburg
2024 - 2025   Research stay at National Institute of Informatics, Japan
2018 - 2021   Master of Science in Solid State Physics at the University of Augsburg
2015 - 2018   Bachelor of Science in Physics at the University of Augsburg
 
 
Rsearch Interests:
  • AI in Sports
  • Physics in Machine Learning
  • Synthetic to Real Generalization
  • Pose Estimation
  • Self-Supervised Learning
 
About Me:  

After completing my Master's degree in Physics, I am now pursuing a PhD in Machine Learning and Computer Vision. I am particularly interested in the intersection of Deep Learning, Computer Vision, and Physics. My current research focuses on the application of Computer Vision in sports. Specifically, I aim to reduce the data dependency of neural networks by integrating physics-based knowledge.

In my free time, I also developed the website  readjapanese.org to help people learn Japanese. With the help of AI, the reading difficulty automatically adapts to your personal learning level.

Publications

2026 | 2025 | 2024 | 2023 | 2022

2026

Marco Riedenauer, Daniel Kienzle, Pratik Mayekar and Rainer Lienhart. 2026. A multi-source ultrasound benchmark revealing the limits of contemporary self-supervised anomaly detection methods. In Paisarn Muneesawang, Supavadee Aramvith, Jianquan Liu, Iole Moccagatta, Ivan Lee, Supatta Viriyavisuthisakul (Eds.). 2026 IEEE 9th International Conference on Multimedia Information Processing and Retrieval (MIPR 2026), Bangkok, Thailand, 9-11 August 2026. IEEE, Piscataway, NJ, 340-346 DOI: 10.1109/MIPR70517.2026.00061
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Julian Lorenz, Vladyslav Kovganko, Elias Kohout, Mrunmai Phatak, Daniel Kienzle and Rainer Lienhart. in press. DSFlash: comprehensive panoptic scene graph generation in realtime. In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR 2026), June 3-7, 2026, Denver, CO, USA. IEEE, Piscataway, NJ, 17388-17398 DOI: 10.48550/arXiv.2603.10538
BibTeX | RIS | DOI

Rainer Lienhart, Daniel Kienzle, Shin'ichi Satoh and Anastasiia Bilinska. in press. Event detection in table tennis videos using 2D keypoints. In ACM MMSports 2026: 9th International ACM Workshop on Multimedia Content Analysis in Sports, November 10th, 2026, Rio de Janeiro, Brazil. ACM, New York, NY
BibTeX | RIS

Nima Rahmanian, Daniel Kienzle, Thomas Gossard, Dvij Kalaria, Rainer Lienhart and S. Shankar Sastry. in press. TT4D: a pipeline and dataset for table tennis 4D reconstruction from monocular videos. In ACM MM 2026. ACM, New York, NY
BibTeX | RIS | URL

Daniel Kienzle, Katja Ludwig, Julian Lorenz, Shin'ichi Satoh and Rainer Lienhart. 2026. Uplifting table tennis: a robust, real-world application for 3D trajectory and spin estimation. In Rama Chellappa, Vitomir Štruc, Srirangaraj Setlur (Eds.). IEEE/CVF Winter Conference on Applications of Computer Vision (WACV) 2026, 6-10 March 2026, Tucson, AZ, USA. IEEE, Piscataway, NJ, 7440-7449 DOI: 10.1109/WACV61042.2026.00718
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2025

Katja Ludwig, Yuliia Oksymets, Robin Schön, Daniel Kienzle and Rainer Lienhart. 2025. Efficient 2D to full 3D human pose uplifting including joint rotations. In 2025 IEEE/CVF International Conference on Computer Vision and Pattern Recognition Workshops (CVPRW), 11-12 June 2025, Nashville, TN, USA. IEEE, Piscataway, NJ, 5842-5851 DOI: 10.1109/CVPRW67362.2025.00583
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Katja Ludwig, Julian Lorenz, Daniel Kienzle, Tuan Bui and Rainer Lienhart. 2025. Leveraging anthropometric measurements to improve human mesh estimation and ensure consistent body shapes. In 2025 IEEE/CVF International Conference on Computer Vision and Pattern Recognition Workshops (CVPRW), 11-12 June 2025, Nashville, TN, USA. IEEE, Piscataway, NJ, 5862-5871 DOI: 10.1109/CVPRW67362.2025.00585
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Robin Schön, Julian Lorenz, Katja Ludwig, Daniel Kienzle and Rainer Lienhart. 2025. MMMS: Multi-Modal Multi-Surface Interactive Segmentation. In Liting Zhou, Klaus Schoeffmann, Duc Tien Dang Nguyen, Dragi Kimovski (Eds.). 2025 IEEE International Conference on Content-Based Multimedia Indexing (IEEE CBMI), 22-24 October 2025, Dublin, Ireland. IEEE, Piscataway, NJ, 1-8 DOI: 10.1109/CBMI66578.2025.11339342
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Robin Schön, Julian Lorenz, Daniel Kienzle and Rainer Lienhart. 2025. SkipClick: combining quick responses and low-level features for interactive segmentation in winter sports contexts. In Jonghyun Choi, Jun-Cheng Chen (Eds.). 2025 IEEE/CVF Winter Conference on Applications of Computer Vision Workshops (WACVW), 28 February - 4 March 2025, Tucson, AZ, USA. IEEE, Piscataway, NJ, 1247-1256 DOI: 10.1109/WACVW65960.2025.00138
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Daniel Kienzle, Robin Schön, Rainer Lienhart and Shin'Ichi Satoh. 2025. Towards ball spin and trajectory analysis in table tennis broadcast videos via physically grounded synthetic-to-real transfer. In 2025 IEEE/CVF International Conference on Computer Vision and Pattern Recognition Workshops (CVPRW), 11-12 June 2025, Nashville, TN, USA. IEEE, Piscataway, NJ, 5832-5841 DOI: 10.1109/CVPRW67362.2025.00582
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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
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Daniel Kienzle, Marco Kantonis, Robin Schön and Rainer Lienhart. 2024. Segformer++: efficient token-merging strategies for high-resolution semantic segmentation. In Guan-Ming Su, Homer Chen, Ming-Ching Chang, Mohan Kankanhalli, Prabhakaran Balakrishnan, Dae Yeol Lee (Eds.). IEEE International Conference on Multimedia Information Processing and Retrieval (MIPR) 2024, San Jose, CA, USA, August 7-9, 2024. IEEE, Piscataway, NJ, 75-81 DOI: 10.1109/MIPR62202.2024.00019
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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
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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
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Robin Schön, Daniel Kienzle and Rainer Lienhart. 2024. WSESeg: introducing a dataset for the segmentation of winter sports equipment with a baseline for interactive segmentation. In 2024 21st International Conference on Content-based Multimedia Indexing (CBMI), 18-20 September 2024, Reykjavik, Iceland. IEEE, Piscataway, NJ, 1-7 DOI: 10.1109/CBMI62980.2024.10859243
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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
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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
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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
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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
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Google Scholar

Supervised Theses

  • Vincent Steiner, Ball Detection in Sports: Comparing Specialized Training Strategies and 2D Human Pose Estimation Techniques, Bachelor thesis, May 2026
  • Alexandra Göppert, From Broadcast to 3D:A Deep Learning Approach for Tennis Trajectory and Spin Estimation, Master thesis, April 2026
  • Anastasiia Bilinska, Event Detection in Table Tennis Videos using 2D Intermediate Representation, Master thesis, April 2026
  • Ulf Jung, Including Camera Information for 2D-to-3D Trajectory Uplifting and Spin Prediction in Table Tennis, Master thesis, April 2026
  • Simon Reithmaier, Leveraging Ball Physics for Improving Camera Calibration in Table Tennis, Master thesis, December 2025
  • Tim Mayer, Removing mmengine and mmcv Dependencies from SegFormer++, Research Module, September 2025
  • Valentin Haug, Automatic Analysis of Camera Dynamics in Table Tennis, Bachelor thesis, August 2025
  • Gregor Böhm, Uncertainity for 3D Ball Localization, Project module, Sept. 2024
  • Felix Lettowsky, Comparison of Different Methods for 3D Ball Localization on Various Datasets, Master thesis, Sept. 2024
  • Norman Szabo, Segmentation Using Attention Masks, Project module, Aug. 2024
  • Marco Kantonis, Analysis of Token-Merging Techniques for Transformer-Based Semantic Segmentation, Master thesis, May 2024
  • Lukas Bayer, Incorporating Token Merging Into Transformers for Efficient Ground State Search of Quantum Spin Models Using minSR, Bachelor thesis, May 2024
  • Simon Reichert, Exploring Image Registration Techniques for XANES Data using Traditional Methods and Machine Learning Techniques, Bachelor thesis, April 2024
  • Felix Lettowsky, Verwendung der Brax-Engine zum Erlernen dreidimensionaler Objektlokalisierung, Projekt module, March 2024
  • Clarissa Dinu-Fröhlich, Erstellung von Modellen zur Semantischen Segmentierung von Körperteilen unter Verwendung von schwachen Segementierungsmasken, Project module, June 2023
  • Jan Claar, Measurement of Droplets in Vaporized Fluids using Machine Learning Techniques, Bachelor thesis, March 2023
  • Jonas Kell, Investigation of transformer architectures for geometrical graph structures and their application to two-dimensional spin systems, Bachelor thesis, Oct. 2022
  • Dennis Knof, Generating artificial datasets with MuJoCo, Internship, Aug. 2022
  • Patrick Hopf, Zeitliche Dynamik in Quantenbillards mit Hilfe neuronaler Netze, Bachelor thesis, Dec. 2021

 

 

 

 

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