Dieses Bild zeigt Jenny Schmalfuß

Jenny Schmalfuß

Frau M. Sc.

Wiss. Mitarbeiterin
Institut für Visualisierung und Interaktive Systeme (VIS)
Abteilung Computer Vision

Kontakt

Universitätsstraße 38
70569 Stuttgart
Deutschland
Raum: 1.465

Fachgebiet

Are all optical flow networks equally vulnerable to adversarial attacks?
Check out our new paper here, which was just accepted at ECCV 2022!

Current Interests

  • Robust motion estimation (optical flow)
  • Adversarial attacks
  • Mathematical concepts for robust neural networks

Background

  • Numerical methods (mostly for PDEs) and scientific computing
  • Computer vision
  • Machine learning and convolutional neural networks
  1. 2022

    1. Schmalfuss, J., Scheurer, E., Zhao, H., Karantzas, N., Bruhn, A., & Labate, D. (2022). Blind image inpainting with sparse directional filter dictionaries for lightweight CNNs. https://doi.org/10.48550/ARXIV.2205.06597
    2. Schmalfuss, J., Scholze, P., & Bruhn, A. (2022). A perturbation constrained adversarial attack for evaluating the robustness of optical flow. https://arxiv.org/abs/2203.13214
  2. 2021

    1. Schmalfuss, J., Riethmüller, C., Altenbernd, M., Weishaupt, K., & Göddeke, D. (2021). Partitioned coupling vs. monolithic block-preconditioning approaches for solving Stokes-Darcy systems. Proceedings of the International Conference on Computational Methods for Coupled Problems in Science and Engineering (COUPLED PROBLEMS). https://doi.org/10.23967/coupled.2021.043
  3. 2016

    1. Wanigasekara, N., Schmalfuss, J., Carlson, D., & Rosenblum, D. S. (2016). A bandit approach for intelligent IoT service composition across heterogeneous smart spaces. Proceedings of the International Conference on the Internet of Things, 121–129. https://doi.org/10.1145/2991561.2991562

Summer 2022:

  • Recent Advances in Computer Vision - Seminar (Supervision)
  • Computer Vision and Intelligent Systems - Colloquium (Organization)

Winter 2021/2022:

  • Computer Vision - Tutorial (Coordinator)
  • Computer Vision and Intelligent Systems - Colloquium (Organization)

Summer 2021:

  • Imaging Science - Tutorial (Coordinator)
  • Recent Advances in Computer Vision - Seminar (Supervision)
  • Computer Vision and Intelligent Systems - Colloquium (Organization)

Winter 2020/2021:

  • Computer Vision - Tutorial (Coordinator)
  • Bildverarbeitung und Computer Vision - Seminar (Supervision)
  • Computer Vision and Intelligent Systems - Colloquium (Organization)

Summer 2020:

  • Imaging Science - Tutorial (Coordinator)

Before Summer Term 2020:

  • Imaging Science - Tutorial (Tutor)
  • Computer Vision - Tutorial (Tutor)

"Preconditioning Techniques for Coupled Stokes Darcy Systems" (Master's thesis, 2019/2020)

"Learning to Transform: Neural Networks with Sparse Directional Filters for Blind Inpainting" (research project in cooperation with the University of Houston, 2018/2019)

"Detection of  Alternative Splicing in Coral Reef Fish Exposed to Climate Change" (research project with the King Abdullah University of Science and Technology, 2017)

"Simulation and Adaptation of Contextual Bandit Algorithms for IoT Service Discovery" (Bachelor's thesis in cooperation with the National University of Singapore, 2016)

"Sparse filters for optical flow robustness". Work in progress. Research Project. University of Stuttgart, 2022.

"An optimization approach for attacking the Horn and Schunck model". Work in progress. Bachelor’s Thesis. University of Stuttgart, 2022.

"Attacking the Horn and Schunck model". Work in progress. Bachelor’s Thesis. University of Stuttgart, 2022.

"Atacking a defended optical flow network". Master’s Thesis. University of Stuttgart, 2022.

"A framework for attacking optical flow networks". Research Project. University of Stuttgart, 2022.

"Switching sparsity: investigating a training time adaptive layer". Research Project. University of Stuttgart, 2021.

"Stability of neural network architectures for optical flow estimation under adversarial attacks". Awarded Best SimTech Bachelor's thesis 2021. Bachelor’s Thesis. University of Stuttgart, 2021.

"Investigating the influence of learning rates on the learning speed of neural networks". Bachelor’s Thesis. University of Stuttgart, 2021.

"Analysing the quality of interframe interpolation with optical flow". Bachelor’s Thesis. University of Stuttgart, 2021.

"Improved RAFT architectures for optical flow estimation". Master’s Thesis. University of Stuttgart, 2021.

Zum Seitenanfang