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Panoramic panoptic segmentation: Towards complete surrounding understanding via unsupervised contrastive learning (Best Paper Award)

Published in 2021 IEEE Intelligent Vehicles Symposium (IV), 2021

Recommended citation: Jaus, Alexander; Yang, Kailun; Stiefelhagen, Rainer; . (2021). "Panoramic panoptic segmentation: Towards complete surrounding understanding via unsupervised contrastive learning." 2021 IEEE Intelligent Vehicles Symposium (IV): 1421-1427.
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Accurate fine-grained segmentation of human anatomy in radiographs via volumetric pseudo-labeling

Published in arXiv, 2023

Recommended citation: Seibold, Constantin; Jaus, Alexander; Fink, Matthias A; Kim, Moon; Reiß, Simon; Herrmann, Ken; Kleesiek, Jens; Stiefelhagen, Rainer; . (2023). "Accurate fine-grained segmentation of human anatomy in radiographs via volumetric pseudo-labeling." arXiv preprint arXiv:2306.03934
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Panoramic panoptic segmentation: Insights into surrounding parsing for mobile agents via unsupervised contrastive learning

Published in IEEE Transactions on Intelligent Transportation Systems, 2023

Recommended citation: Jaus, Alexander; Yang, Kailun; Stiefelhagen, Rainer; . (2023). "Panoramic panoptic segmentation: Insights into surrounding parsing for mobile agents via unsupervised contrastive learning." IEEE Transactions on Intelligent Transportation Systems. 24(4): 4438-4453.
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Towards unifying anatomy segmentation: automated generation of a full-body ct dataset via knowledge aggregation and anatomical guidelines

Published in arXiv, 2023

Recommended citation: Jaus, Alexander; Seibold, Constantin; Hermann, Kelsey; Walter, Alexandra; Giske, Kristina; Haubold, Johannes; Kleesiek, Jens; Stiefelhagen, Rainer; . (2023). "Towards unifying anatomy segmentation: automated generation of a full-body ct dataset via knowledge aggregation and anatomical guidelines." arXiv preprint arXiv:2307.13375..
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Anatomy-guided Pathology Segmentation

Published in International Conference on Medical Image Computing and Computer-Assisted Intervention, 2024

Recommended citation: Jaus, Alexander; Seibold, Constantin; Reiß, Simon; Heine, Lukas; Schily, Anton; Kim, Moon; Bahnsen, Fin Hendrik; Herrmann, Ken; Stiefelhagen, Rainer; Kleesiek, Jens; . (2024). "Anatomy-guided Pathology Segmentation." International Conference on Medical Image Computing and Computer-Assisted Intervention: 3-13.
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Data Diet: Can Trimming PET/CT Datasets Enhance Lesion Segmentation?

Published in 🥈 MICCAI 2024 AutoPET Datacentric Track, 2024

Recommended citation: Jaus, Alexander; Reiß, Simon; Kleesiek, Jens; Stiefelhagen, Rainer; . (2024). "Data Diet: Can Trimming PET/CT Datasets Enhance Lesion Segmentation?." 🥈 MICCAI 2024 AutoPET Datacentric Track: nan.
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Every Component Counts: Rethinking the Measure of Success for Medical Semantic Segmentation in Multi-Instance Segmentation Tasks

Published in Proceedings of the AAAI Conference on Artificial Intelligence 2025, 2024

Recommended citation: Jaus, Alexander; Seibold, Constantin; Reiß, Simon; Marinov, Zdravko; Li, Keyi; Ye, Zeling; Krieg, Stefan; Kleesiek, Jens; Stiefelhagen, Rainer; . (2024). "Every Component Counts: Rethinking the Measure of Success for Medical Semantic Segmentation in Multi-Instance Segmentation Tasks." Proceedings of the AAAI Conference on Artificial Intelligence 2025.
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Filters, thresholds, and geodesic distances for scribble-based interactive segmentation of medical images

Published in CVPR: MedSAM Medical Image Segmentation Challenge, 2024

Recommended citation: Marinov, Zdravko; Jaus, Alexander; Kleesiek, Jens; Stiefelhagen, Rainer; . (2024). "Filters, thresholds, and geodesic distances for scribble-based interactive segmentation of medical images." Medical Image Segmentation Challenge: 39-56.
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FootCapture: Towards an AR-based System for 3D Foot Object Acquisition through Photogrammetry

Published in Medical Imaging with Deep Learning, 2024

Recommended citation: Khan-Blouki, Valentin; Seiz, Franziska; Walter, Nicolas; Jaus, Alexander; Marinov, Zdravko; Luijten, Gijs; Egger, Jan; Seibold, Constantin Marc; Solte, Dirk; Kleesiek, Jens; Stiefelhagen, Rainer. (2024). "FootCapture: Towards an AR-based System for 3D Foot Object Acquisition through Photogrammetry." Medical Imaging with Deep Learning
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LIMIS: Towards Language-based Interactive Medical Image Segmentation (Oral)

Published in International Symposium on Biomedical Imaging (ISBI), 2024

Recommended citation: Heinemann, L., Jaus, A., Marinov, Z., Kim, M., Spadea, M. F., Kleesiek, J., & Stiefelhagen, R. (2025, April). LIMIS: Towards Language-Based Interactive Medical Image Segmentation. In 2025 IEEE 22nd International Symposium on Biomedical Imaging (ISBI) (pp. 1-5). IEEE.
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Muscles in time: Learning to understand human motion in-depth by simulating muscle activations

Published in Advances in Neural Information Processing Systems, 2024

Recommended citation: Schneider, David; Reiß, Simon; Kugler, Marco; Jaus, Alexander; Peng, Kunyu; Sutschet, Susanne; Sarfraz, M Saquib; Matthiesen, Sven; Stiefelhagen, Rainer; . (2024). "Muscles in time: Learning to understand human motion in-depth by simulating muscle activations." Advances in Neural Information Processing Systems. 37: 67251-67281.
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Taking a Step Back: Revisiting Classical Approaches for Efficient Interactive Segmentation of Medical Images

Published in CVPR: MedSAM Medical Image Segmentation Challenge, 2024

Recommended citation: Marinov, Zdravko; Jaus, Alexander; Kleesiek, Jens; Stiefelhagen, Rainer; . (2024). "Taking a Step Back: Revisiting Classical Approaches for Efficient Interactive Segmentation of Medical Images." Medical Image Segmentation Challenge: 101-125.
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Towards Unifying Anatomy Segmentation: Automated Generation of a Full-Body CT Dataset

Published in 2024 IEEE International Conference on Image Processing (ICIP), 2024

Recommended citation: Jaus, Alexander; Seibold, Constantin; Hermann, Kelsey; Shahamiri, Negar; Walter, Alexandra; Giske, Kristina; Haubold, Johannes; Kleesiek, Jens; Stiefelhagen, Rainer; . (2024). "Towards Unifying Anatomy Segmentation: Automated Generation of a Full-Body CT Dataset." 2024 IEEE International Conference on Image Processing (ICIP): 41-47.
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Medshapenet–a large-scale dataset of 3d medical shapes for computer vision

Published in Biomedical Engineering/Biomedizinische Technik, 2025

Recommended citation: Li, Jianning; Zhou, Zongwei; Yang, Jiancheng; Pepe, Antonio; Gsaxner, Christina; Luijten, Gijs; Qu, Chongyu; Zhang, Tiezheng; Chen, Xiaoxi; Li, Wenxuan; . (2025). "Medshapenet–a large-scale dataset of 3d medical shapes for computer vision." Biomedical Engineering/Biomedizinische Technik. 70(1): 71-90.
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Talk 1 on Relevant Topic in Your Field

Published: March 01, 2012

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Tutorial 1 on Relevant Topic in Your Field

Published: March 01, 2013

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Talk 2 on Relevant Topic in Your Field

Published: February 01, 2014

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Conference Proceeding talk 3 on Relevant Topic in Your Field

Published: March 01, 2014

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Teaching Assistant for the Course Deep Learning for Computer Vision

Graduate course, Karlsruhe Institute of Technology, 2012

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Teaching experience 2

Workshop, University 1, Department, 2015

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