I am a postdoctoral researcher in the Visual Inference Lab at TU Darmstadt supervised by Prof. Dr. Stefan Roth. Previously, I was a Ph.D. candidate supervised by Prof. Dr. Ing. Margret Keuper at the University of Mannheim in cooperation with Prof. Dr. Janis Keuper at IMLA, Offenburg.
My research primarily focuses on Computer Vision, leveraging insights from classical signal processing and cognitive neuroscience to enhance understanding and performance.
News
07/2025 I joined the Visual Inference Lab, led by Stefan Roth, as a postdoctoral researcher.
07/2025 I successfully defended my PhD thesis “Multifaceted Analysis of Deep Convolutional Neural Networks and Novel Fourier Modules” at the University of Mannheim!
05/2025 I presented our paper As large as it gets – Studying Infinitely Large Convolutions via Neural Implicit Frequency Filters at ICLR 2025!
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