About
My interests are Computer Vision and Machine Learning. I investigated motion in videos — its modeling and importance — in deep video understanding models during my PhD with my supervisors Thomas Pock, and Richard Wildes. Additionally, I was also lucky enough to have wonderful collaborators and projects that allowed me to work on other topics such as denoising, generative modeling, and implicit neural representations.
Before that, I worked at CERN for the CMS experiment on performance critical monitoring and analysis software.
PhD at Vision, Learning & Optimization Group - ICG - TU Graz
Visiting Researcher at Center for Vision Research - York University - Toronto
Technical Student at CMS Experiment - CERN - Geneva
Publications
Dissertation
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Deep Learning in Video Understanding:
The Role of Motion in Action Recognition Defended in 2024 at TU Graz, Supervisor Thomas Pock |
CVPR
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Selective, Interpretable, and Motion Consistent Privacy Attribute Obfuscation for Action Recognition
2024 Conference on Computer Vision and Pattern Recognition
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GCPR
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Score-Based Generative Models for Medical Image Segmentation using Signed Distance Functions
2023 German Conference on Computer Vision
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WACV
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Lightweight Video Denoising using Aggregated Shifted Window Attention
2023 Winter Conference on Applications of Computer Vision
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ECCV
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Is Appearance Free Action Recognition Possible?
2022 European Conference on Computer Vision
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OAGM
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A study on robust feature representations for grain density estimates in austenitic steel
2021 Computer Vision and Pattern Analysis Across Domains
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OAGM
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On the Influence of Beta Cell Granule Counting for Classification in Type 1 Diabetes
2021 Computer Vision and Pattern Analysis Across Domains
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WACV
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Representing Objects in Video as Space-Time Volumes by Combining Top-Down and Bottom-Up Processes
2020 Winter Conference on Applications of Computer Vision
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Miscellaneous
Teaching
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Physicalization
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Physicalization
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Physicalization
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Nerd Alert
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