Fabian Herzog

I am a research assistant and PhD student at the Institute of Human-Machine Communication of the Technical University of Munich, Germany. My main research is in computer vision and pattern recognition.

Prior to joining TU Munich, I did my Master's in Scientific Computing in Göttingen with a focus on mathematical image processing.

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Research

My research is on machine learning and computer vision for video processing. Here are my recent projects and papers:

Face Aggregation Network For Video Face Recognition
S. Hörmann, Z. Chao, M. Knoche, F. Herzog, and G. Rigoll
IEEE International Conference on Image Processing (ICIP), 2021
IEEE Article

***Accepted for ICIP 2021***

We suggest a permutation invariant U-Net architecture capable of processing an arbitrary number of frames in video face recognition.

GaitGraph: Graph Convolutional Network for Skeleton-Based Gait Recognition
T. Teepe, A. Khan, J. Gilg, F. Herzog, S. Hörmann, and G. Rigoll
IEEE International Conference on Image Processing (ICIP), 2021
arXiv / code

***Accepted for ICIP 2021***

A novel Graph Convolutional Network (GCN) to obtain a modern model-based approach for gait recognition.

Lightweight Multi-Branch Network for Person Re-Identification
F. Herzog, X. Ji, T. Teepe, S. Hörmann, J. Gilg, and G. Rigoll
IEEE International Conference on Image Processing (ICIP), 2021
arXiv / code

***Accepted for ICIP 2021***

Lightweight network that combines global, part-based, and channel features in a unified multi-branch architecture.
Dissected 3D CNNs: Temporal Skip Connections for Efficient Online Video Processing
O. Köpüklü, S. Hörmann, F. Herzog, H. Cevikalp, and G. Rigoll
arXiv, 2020
arXiv / code

We propose dissected 3D CNNs to address several serious handicaps of 3D ResNet models during online operation.
Comparative Analysis of CNN-Based Spatiotemporal Reasoning in Videos
O. Köpüklü, F. Herzog, and G. Rigoll
ICPR International Workshops and Challenges. ICPR 2021.
arXiv / code / video / publication

***Accepted for ICPR International Workshops 2021***

A comparative analysis of different spatiotemporal modeling techniques for action and gesture recognition.
Teaching

Summer 2021

Winter 2020 / 2021

  • Practical Course on Audio and Image Processing

Summer 2020

  • Human-Machine Communication II (Exercises)
  • Musical Acoustics (Assistance) (canceled due to COVID-19)

Winter 2019 / 2020

  • Practical Course on Audio and Image Processing
  • Practical Course on Systems Engineering

Summer 2019

  • Human-Machine Communication II (Exercises)

Supervision

I'm supervising theses in the areas of computer vision and pattern recognition. Due to the high number of applications, I can only respond to complete applications with current CV, transcript of records and motivation letter. I do not supervise external theses.
Professional Service
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