Rafael Sterzinger is a PhD student at the Computer Vision Lab, Institute of Visual Computing & Human-Centered Technology, TU Wien, Austria.
Education |
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| 2023 – | Dr., TU Wien.
Thesis title: . Thesis advisor: Robert Sablatnig |
| 2020 – 2023 | MSc., ETH Zürich, Computer Science.
Thesis title: . Thesis advisor: Andreas Krause |
| 2017 – 2020 | BSc., TU Wien, Business Informatics. |
Profile
Google Scholar | ArXiv | ORCID | LinkedIn
Publications
R. Sterzinger, M. Peer, R. Sablatnig, (2024). “Few-Shot Segmentation of Historical Maps via Linear Probing of Vision Foundation Models”, (Submitted)
J. Strohmayer, R. Sterzinger, M. Wödlinger, M. Kampel, (2024). “DATTA: Domain-Adversarial Test-Time Adaptation for Cross-Domain WiFi-Based Human Activity Recognition”, (Submitted)
R. Sterzinger, W. Koch, R. Hoch, (2024). “Exploring Machine Learning for Faster Mapping and Scheduling of Automotive Applications on ADAS Platforms”, International Conference on Machine Learning and Applications (ICMLA), Miami, FL, USA, pp. 851–855, doi: 10.1109/ICMLA61862.2024.00123
R. Sterzinger, C. Stippel, R. Sablatnig, (2024). “Fusing Forces: Deep-Human-Guided Refinement of Segmentation Masks”, In: Antonacopoulos, A., Chaudhuri, S., Chellappa, R., Liu, C.L., Bhattacharya, S., Pal, U. (eds), Pattern Recognition – ICPR 2024, Lecture Notes in Computer Science, vol. 15312, Springer, Kolkata, India, pp. 154–169, doi: 10.1007/978-3-031-78198-8_11
J. Strohmayer, R. Sterzinger, C. Stippel, M. Kampel, (2024). “Through-Wall Imaging Based On WiFi Channel State Information”, 2024 IEEE International Conference on Image Processing (ICIP), Abu Dhabi, UAE, pp. 4000–4006, doi: 10.1109/ICIP51287.2024.10647775
R. Sterzinger, S. Brenner, R. Sablatnig, (2024). “Drawing the Line: Deep Segmentation for Extracting Art from Ancient Etruscan Mirrors”, In: Barney Smith, E.H., Liwicki, M., Peng, L. (eds), Document Analysis and Recognition – ICDAR 2024, Lecture Notes in Computer Science, vol. 14806, Springer, Athens, Greece, pp. 39–56, doi: 10.1007/978-3-031-70543-4_3
C. Stippel, R. Sterzinger, D. Sengl, A. Bratukhin, M. Kobelrausch, S. Wilker, T. Sauter, (2024). “Online HVAC Optimization under Comfort Constraints via Reinforcement Learning”, 2024 IEEE 7th International Conference on Industrial Cyber-Physical Systems (ICPS), St. Louis, MO, USA, pp. 1–6, doi: 10.1109/ICPS59941.2024.10640003
C. Stippel, T. Heitzinger, R. Sterzinger, M. Kampel, (2024). “Closing the Gap in Human Behavior Analysis: A Pipeline for Synthesizing Trimodal Data”, 2024 IEEE International Conference on Pervasive Computing and Communications Workshops and other Affiliated Events (PerCom Workshops), Biarritz, France, pp. 793–798, doi: 10.1109/PerComWorkshops59983.2024.10503351
R. Sterzinger, J. Poland, M. B. Paulus, D. Chételat, (2023). “Learning to Predict Security Constraints for Large-Scale Unit Commitment Problems”, 2023 IEEE PES Innovative Smart Grid Technologies Europe (ISGT EUROPE), Grenoble, France, pp. 1–5, doi: 10.1109/ISGTEUROPE56780.2023.10407236 (Originating from Master’s Thesis)
C. Stippel, T. Heitzinger, R. Sterzinger, M. Kampel, (2023). “From RGB to Depth and Thermal: Mapping between Modalities to Alleviate Data Scarcity”, Proceedings of the Austrian Association for Pattern Recognition (AAPR) Joint Austrian Computer Vision and Robotics Workshop, Vienna, Austria. (Accepted)