• Machine Learning
• Deep Learning
• 2D/3D Human Pose Estimation
• Human Pose Estimation in Sports Applications
• Video Indexing and Event Detection

Deep Sports Pose: Automatische zeitkontinuierliche Bestimmung markanter Körperpunkte auf Sportlern sowie daraus abgeleiteter Ereignisse in Videos.      

• Moritz Einfalt, Katja Ludwig, Rainer Lienhart
  Uplift and Upsample: Efficient 3D Human Pose Estimation with Uplifting Transformers
  IEEE/CVF Winter Conference on Applications of Computer Vision (WACV). Waikoloa, USA, January 2023.[ arXiv][ CVF][ GitHub]

• Philipp Harzig, Moritz Einfalt, Rainer Lienhart
  Synchronized Audio-Visual Frames With Fractional Positional Encoding for Transformers in Video-to-Text Translation.
  IEEE International Conference on Image Processing (ICIP). Bordeaux, France October 2022. [ PDF]
• Nikolas Klug, Moritz Einfalt, Stephan Brehm, Rainer Lienhart.
  Error Bounds of Projection Models in Weakly Supervised 3D Human Pose Estimation.
  2020 International Conference on 3D Vision (3DV), IEEE. Fukuoka, Japan, November 2020. [ arXiv  IEEE  PDF]
• Moritz Einfalt, Rainer Lienhart.
  Decoupling Video and Human Motion: Towards Practical Event Detection in Athlete Recordings.
  The IEEE Conference on Computer Vision and Pattern Recognition (CVPR) Workshops 2020. Seattle, WA, USA, June 2020. [ arXiv  CVF  PDF]
• Moritz Einfalt, Charles Dampeyrou, Dan Zecha, Rainer Lienhart.
  Frame-level Event Detection in Athletics Videos with Pose-based Convolutional Sequence Networks.
  Second International ACM Workshop on Multimodal Content Analysis in Sports (ACM MMSports'19), part of ACM Multimedia (ACMMM) 2019. Nice, France, October 2019. [ ACM DL  PDF]
• Dan Zecha, Moritz Einfalt, Rainer Lienhart. 
  Refining Joint Locations for Human Pose Tracking in Sports Videos. 
  IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) Workshops 2019. Long Beach, CA, USA, June 2019. [ CVF PDF]
• Moritz Einfalt, Rainer Lienhart, Matthew Lee, Lyndon Kennedy.
  Detecting Speech Impairments from Temporal Visual Facial Features of Aphasia Patients.
  IEEE MIPR 2019, San José, CA, USA, March 2019. [ IEEE  PDF]
• Rainer Lienhart, Moritz Einfalt, Dan Zecha.
  Mining Automatically Estimated Poses from Video Recordings of Top Athletes.
  IJCSS, December 2018. [ IJCSS   PDF]
• Dan Zecha, Christian Eggert, Moritz Einfalt, Stephan Brehm, Rainer Lienhart.
  A Convolutional Sequence to Sequence Model for Multimodal Dynamics Prediction in Ski Jumps.
  First International ACM Workshop on Multimodal Content Analysis in Sports (ACM MMSports'18), part of ACM Multimedia 2018. Seoul, Korea, October 2018. [ PDF]
• Dan Zecha, Moritz Einfalt, Christian Eggert, Rainer Lienhart.
  Kinematic Pose Rectification for Performance Analysis and Retrieval in Sports.
  IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) Workshops 2018. Salt Lake City, USA, June 2018. [ PDF]
• Moritz Einfalt, Dan Zecha, Rainer Lienhart.
  Activity-conditioned continuous human pose estimation for performance analysis of athletes using the example of swimming.
  IEEE Winter Conference on Applications of Computer Vision 2018 (WACV18), Lake Tahoe, NV, USA, March 2018. [ arXiv  IEEE  PDF]

• Moritz Einfalt, Dan Zecha, Rainer Lienhart.
  Automatische zeitkontinuierliche Bestimmung markanter Körperpunkte auf Sportlern sowie daraus abgeleiteter Ereignisse in Videos.
  13. Tagung der dvs-Kommision Leichtathletik. TU Dortmund, Germany, June 28, 2019.

• Moritz Einfalt. Human Motion Analysis on Visual Data - Shaping 2D Human Pose Estimation into a Tool for Sport and Medical Applications. Dissertation, Universität Augsburg, 26. April 2024. ( Offiziell)
• Moritz Einfalt, Convolutional Pose Machines – Improvements, Extensions and Applications.
  Master Thesis, June 2017. [ PDF]

• Moritz Einfalt, Decision Forests for Regression.
  Bachelor Thesis, September 2014. [ PDF]

• WS 2022: Grundlagen der Signalverarbeitung und des Maschinellen Lernens (wechselnde Dozenten)
• WS 2022: Advanced Machine Learning and Computer Vision
• SS 2022: Probabilistic Robotics
• WS 2021: Advanced Machine Learning and Computer Vision
• SS 2021: Bayesian Networks
• WS 2020: Advanced Machine Learning and Computer Vision
• SS 2020: Bayesian Networks
• WS 2019: Grundlagen der Signalverarbeitung und des Maschinellen Lernens für Medizininformatiker
• WS 2019: Probabilistic Robotics
• WS 2019: Seminar: Multimediale Datenverarbeitung
• SS 2019: Bayesian Networks
• SS 2019: Seminar: Multimedia und Maschinelles Sehen
• WS 2018:  Multimedia Grundlagen I
• SS 2018: Bayesian Networks
• WS 2017:  Multimedia Grundlagen I (wechselnde Dozenten)