Actively seeking Postdoc Opportunities
I am a final-year Ph.D. student with a keen interest in the field of Computer Vision. Under the supervision of Prof. Dr. Ing. Margret Keuper at the University of Mannheim in cooperation with Prof. Dr. Janis Keuper at IMLA, Offenburg.
My research focuses on signal processing fundamentals, which I apply in modern deep learning approaches to create innovative solutions that push the boundaries of what’s possible. Especially, my current focus lies at the intersection of signal processing fundamentals and convolutional neural networks (CNNs). Through extensive analysis of various components within CNNs, I aim to leverage my signal processing expertise to address current limitations and optimize their performance. Adversarial attacks, in particular, provide a valuable means to assess these vulnerabilities of CNNs and refine their robustness for real-world tasks. As such, I am equally intrigued by adversarial attacks and defences.
News
10/2024 I presented my work about enhancing modern computer vision with classic signal processing techniques at the Doctoral Consortium at ECCV 2024 and was mentored by Elisa Ricci.
09/2024 I gave a talk about our work on Neural Implicit Frequency Filters at the DWS Colloquium at University of Mannheim.
09/2024 I was honored as Outstanding Reviewer at ECCV 2024!
09/2024 Our paper Improving Feature Stability during Upsampling – Spectral Artifacts and the Importance of Spatial Context got accepted at ECCV 2024!
08/2024 I gave a talk about our Neural Implicit Frequency Filters and their application in studying the optimal filter size for a given network at Or Litany’s group at the Technion.
05/2024 Our paper As large as it gets – Studying Infinitely Large Convolutions via Neural Implicit Frequency Filters got accepted at TMLR with Featured Certification!
05/2024 I was a visiting researcher at Tampere University in the computer vision group of Prof. Dr. Esa Rathu for the three month!
08/2023 Our paper On the unreasonable vulnerability of transformers for image restoration-and an easy fix got accepted to the ICCV 2023 Workshop on Adversarial Robustness In the Real World!
09/2022 Our paper Robust Models are less Over-Confident got accepted at NeurIPS 2022!
07/2022 Our paper FrequencyLowCut Pooling–Plug & Play against Catastrophic Overfitting got accepted at ECCV 2022!
06/2022 Our paper Aliasing and adversarial robust generalization of CNNs got accepted at ECML 2022!
Publications
As large as it gets – Studying Infinitely Large Convolutions via Neural Implicit Frequency Filters
J. Grabinski, J. Keuper, M. Keuper
TMLR 2024 (Featured Certification)
PDF | Code
Improving Feature Stability during Upsampling – Spectral Artifacts and the Importance of Spatial Context
S. Agnihotri, J. Grabinski, M. Keuper
ECCV 2024
PDF
On the unreasonable vulnerability of transformers for image restoration-and an easy fix
S. Agnihotri, KV. Gandikota, J. Grabinski, P. Chandramouli, M. Keuper
ICCV 2023, Workshop on Adversarial Robustness In the Real World
PDF
Robust Models are less Over-Confident
J. Grabinski, P. Gavrikov, J. Keuper, M. Keuper
NeurIPS 2022
PDF | Code
FrequencyLowCut Pooling–Plug & Play against Catastrophic Overfitting
J. Grabinski, S. Jung, J. Keuper, M. Keuper
ECCV 2022
PDF | Code
Aliasing and adversarial robust generalization of CNNs
J. Grabinski, J. Keuper, M. Keuper
ECML 2022
PDF
Robust Models are less Over-Confident
J. Grabinski, P. Gavrikov, J. Keuper, M. Keuper
ICML 2022, Workshop New Frontiers in Adversarial Machine Learning
PDF
Aliasing coincides with CNNs vulnerability towards adversarial attacks
J. Grabinski, J. Keuper, M. Keuper
AAAI 2022, Workshop on Adversarial Machine Learning and Beyond
PDF