Saved in:
| Main Authors: | Agnihotri, Shashank, Schader, David, Sharei, Nico, Kaçar, Mehmet Ege, Keuper, Margret |
|---|---|
| Format: | Preprint |
| Published: |
2025
|
| Subjects: | |
| Online Access: | https://arxiv.org/abs/2505.04835 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
SemSegBench & DetecBench: Benchmarking Reliability and Generalization Beyond Classification
by: Agnihotri, Shashank, et al.
Published: (2025)
by: Agnihotri, Shashank, et al.
Published: (2025)
DispBench: Benchmarking Disparity Estimation to Synthetic Corruptions
by: Agnihotri, Shashank, et al.
Published: (2025)
by: Agnihotri, Shashank, et al.
Published: (2025)
CosPGD: an efficient white-box adversarial attack for pixel-wise prediction tasks
by: Agnihotri, Shashank, et al.
Published: (2023)
by: Agnihotri, Shashank, et al.
Published: (2023)
Improving Feature Stability during Upsampling -- Spectral Artifacts and the Importance of Spatial Context
by: Agnihotri, Shashank, et al.
Published: (2023)
by: Agnihotri, Shashank, et al.
Published: (2023)
RobustSpring: Benchmarking Robustness to Image Corruptions for Optical Flow, Scene Flow and Stereo
by: Oei, Victor, et al.
Published: (2025)
by: Oei, Victor, et al.
Published: (2025)
Smart Eyes for Silent Threats: VLMs and In-Context Learning for THz Imaging
by: Poggi, Nicolas, et al.
Published: (2025)
by: Poggi, Nicolas, et al.
Published: (2025)
Faithful, Interpretable Chest X-ray Diagnosis with Anti-Aliased B-cos Networks
by: Kleinmann, Marcel, et al.
Published: (2025)
by: Kleinmann, Marcel, et al.
Published: (2025)
Images as Tables: In-Context Learning with TabPFN for Low-Data Detection of AI-Generated Images
by: Walter, Jan Philip, et al.
Published: (2026)
by: Walter, Jan Philip, et al.
Published: (2026)
How Do Training Methods Influence the Utilization of Vision Models?
by: Gavrikov, Paul, et al.
Published: (2024)
by: Gavrikov, Paul, et al.
Published: (2024)
Beware of Aliases -- Signal Preservation is Crucial for Robust Image Restoration
by: Agnihotri, Shashank, et al.
Published: (2024)
by: Agnihotri, Shashank, et al.
Published: (2024)
AIM: Amending Inherent Interpretability via Self-Supervised Masking
by: Alshami, Eyad, et al.
Published: (2025)
by: Alshami, Eyad, et al.
Published: (2025)
Vision At Night: Exploring Biologically Inspired Preprocessing For Improved Robustness Via Color And Contrast Transformations
by: Stracke, Lorena, et al.
Published: (2025)
by: Stracke, Lorena, et al.
Published: (2025)
RAWDet-7: A Multi-Scenario Benchmark for Object Detection and Description on Quantized RAW Images
by: Fatima, Mishal, et al.
Published: (2026)
by: Fatima, Mishal, et al.
Published: (2026)
GeoDiv: Framework For Measuring Geographical Diversity In Text-To-Image Models
by: Basu, Abhipsa, et al.
Published: (2026)
by: Basu, Abhipsa, et al.
Published: (2026)
$γ$-Quant: Towards Learnable Quantization for Low-bit Pattern Recognition
by: Fatima, Mishal, et al.
Published: (2025)
by: Fatima, Mishal, et al.
Published: (2025)
Deepfakes: we need to re-think the concept of "real" images
by: Keuper, Janis, et al.
Published: (2025)
by: Keuper, Janis, et al.
Published: (2025)
Edge Reliability Gap in Vision-Language Models: Quantifying Failure Modes of Compressed VLMs Under Visual Corruption
by: Erol, Mehmet Kaan
Published: (2026)
by: Erol, Mehmet Kaan
Published: (2026)
As large as it gets: Learning infinitely large Filters via Neural Implicit Functions in the Fourier Domain
by: Grabinski, Julia, et al.
Published: (2023)
by: Grabinski, Julia, et al.
Published: (2023)
Is Your HD Map Constructor Reliable under Sensor Corruptions?
by: Hao, Xiaoshuai, et al.
Published: (2024)
by: Hao, Xiaoshuai, et al.
Published: (2024)
Stylized Synthetic Augmentation further improves Corruption Robustness
by: Siedel, Georg, et al.
Published: (2025)
by: Siedel, Georg, et al.
Published: (2025)
Unfolding Local Growth Rate Estimates for (Almost) Perfect Adversarial Detection
by: Lorenz, Peter, et al.
Published: (2022)
by: Lorenz, Peter, et al.
Published: (2022)
Corrupted but Not Broken: Understanding and Mitigating the Negative Impacts of Corrupted Data in Visual Instruction Tuning
by: Gou, Yunhao, et al.
Published: (2025)
by: Gou, Yunhao, et al.
Published: (2025)
Know Yourself Better: Diverse Object-Related Features Improve Open Set Recognition
by: Xu, Jiawen, et al.
Published: (2024)
by: Xu, Jiawen, et al.
Published: (2024)
Benchmarking Robustness of Endoscopic Depth Estimation with Synthetically Corrupted Data
by: Wang, An, et al.
Published: (2024)
by: Wang, An, et al.
Published: (2024)
Is RobustBench/AutoAttack a suitable Benchmark for Adversarial Robustness?
by: Lorenz, Peter, et al.
Published: (2021)
by: Lorenz, Peter, et al.
Published: (2021)
Examining the Impact of Optical Aberrations to Image Classification and Object Detection Models
by: Müller, Patrick, et al.
Published: (2025)
by: Müller, Patrick, et al.
Published: (2025)
Corner Cases: How Size and Position of Objects Challenge ImageNet-Trained Models
by: Fatima, Mishal, et al.
Published: (2025)
by: Fatima, Mishal, et al.
Published: (2025)
Investigating the Corruption Robustness of Image Classifiers with Random Lp-norm Corruptions
by: Siedel, Georg, et al.
Published: (2023)
by: Siedel, Georg, et al.
Published: (2023)
Fix your downsampling ASAP! Be natively more robust via Aliasing and Spectral Artifact free Pooling
by: Grabinski, Julia, et al.
Published: (2023)
by: Grabinski, Julia, et al.
Published: (2023)
Detecting AutoAttack Perturbations in the Frequency Domain
by: Lorenz, Peter, et al.
Published: (2021)
by: Lorenz, Peter, et al.
Published: (2021)
I Spy With My Little Eye: A Minimum Cost Multicut Investigation of Dataset Frames
by: Prasse, Katharina, et al.
Published: (2024)
by: Prasse, Katharina, et al.
Published: (2024)
Target-Guided Adversarial Point Cloud Transformer Towards Recognition Against Real-world Corruptions
by: Wang, Jie, et al.
Published: (2024)
by: Wang, Jie, et al.
Published: (2024)
Analysing the Robustness of Vision-Language-Models to Common Corruptions
by: Usama, Muhammad, et al.
Published: (2025)
by: Usama, Muhammad, et al.
Published: (2025)
Benchmarking the Robustness of UAV Tracking Against Common Corruptions
by: Liu, Xiaoqiong, et al.
Published: (2024)
by: Liu, Xiaoqiong, et al.
Published: (2024)
A High-Quality Robust Diffusion Framework for Corrupted Dataset
by: Dao, Quan, et al.
Published: (2023)
by: Dao, Quan, et al.
Published: (2023)
DRIVE-C: A Controlled Corruption Dataset for Autonomous Driving
by: Aher, Shiva
Published: (2026)
by: Aher, Shiva
Published: (2026)
TRIX- Trading Adversarial Fairness via Mixed Adversarial Training
by: Medi, Tejaswini, et al.
Published: (2025)
by: Medi, Tejaswini, et al.
Published: (2025)
Informed Mixing -- Improving Open Set Recognition via Attribution-based Augmentation
by: Xu, Jiawen, et al.
Published: (2025)
by: Xu, Jiawen, et al.
Published: (2025)
Towards Class-wise Robustness Analysis
by: Medi, Tejaswini, et al.
Published: (2024)
by: Medi, Tejaswini, et al.
Published: (2024)
FAIR-TAT: Improving Model Fairness Using Targeted Adversarial Training
by: Medi, Tejaswini, et al.
Published: (2024)
by: Medi, Tejaswini, et al.
Published: (2024)
Similar Items
-
SemSegBench & DetecBench: Benchmarking Reliability and Generalization Beyond Classification
by: Agnihotri, Shashank, et al.
Published: (2025) -
DispBench: Benchmarking Disparity Estimation to Synthetic Corruptions
by: Agnihotri, Shashank, et al.
Published: (2025) -
CosPGD: an efficient white-box adversarial attack for pixel-wise prediction tasks
by: Agnihotri, Shashank, et al.
Published: (2023) -
Improving Feature Stability during Upsampling -- Spectral Artifacts and the Importance of Spatial Context
by: Agnihotri, Shashank, et al.
Published: (2023) -
RobustSpring: Benchmarking Robustness to Image Corruptions for Optical Flow, Scene Flow and Stereo
by: Oei, Victor, et al.
Published: (2025)