Image de couverture de livre

FAIR-TAT: Improving Model Fairness Using Targeted Adversarial Training

Fuente: arXiv

Enregistré dans:

Détails bibliographiques
Auteurs principaux:	Medi, Tejaswini, Jung, Steffen, Keuper, Margret
Format:	Preprint
Publié:	2024
Sujets:	Machine Learning Computer Vision and Pattern Recognition
Accès en ligne:	Acceder al recurso
Tags:	Ajouter un tag Pas de tags, Soyez le premier à ajouter un tag!

Documents similaires

TRIX- Trading Adversarial Fairness via Mixed Adversarial Training
par: Medi, Tejaswini, et autres
Publié: (2025)

Towards Class-wise Robustness Analysis
par: Medi, Tejaswini, et autres
Publié: (2024)

Missing Fine Details in Images: Last Seen in High Frequencies
par: Medi, Tejaswini, et autres
Publié: (2025)

3D-WAG: Hierarchical Wavelet-Guided Autoregressive Generation for High-Fidelity 3D Shapes
par: Medi, Tejaswini, et autres
Publié: (2024)

Know Yourself Better: Diverse Object-Related Features Improve Open Set Recognition
par: Xu, Jiawen, et autres
Publié: (2024)

How Do Training Methods Influence the Utilization of Vision Models?
par: Gavrikov, Paul, et autres
Publié: (2024)

Corner Cases: How Size and Position of Objects Challenge ImageNet-Trained Models
par: Fatima, Mishal, et autres
Publié: (2025)

Informed Mixing -- Improving Open Set Recognition via Attribution-based Augmentation
par: Xu, Jiawen, et autres
Publié: (2025)

Adversarial Supervision Makes Layout-to-Image Diffusion Models Thrive
par: Li, Yumeng, et autres
Publié: (2024)

Can We Talk Models Into Seeing the World Differently?
par: Gavrikov, Paul, et autres
Publié: (2024)

Faithful, Interpretable Chest X-ray Diagnosis with Anti-Aliased B-cos Networks
par: Kleinmann, Marcel, et autres
Publié: (2025)

Local Spherical Harmonics Improve Skeleton-Based Hand Action Recognition
par: Prasse, Katharina, et autres
Publié: (2023)

CosPGD: an efficient white-box adversarial attack for pixel-wise prediction tasks
par: Agnihotri, Shashank, et autres
Publié: (2023)

Beware of Aliases -- Signal Preservation is Crucial for Robust Image Restoration
par: Agnihotri, Shashank, et autres
Publié: (2024)

Divide & Bind Your Attention for Improved Generative Semantic Nursing
par: Li, Yumeng, et autres
Publié: (2023)

Fix your downsampling ASAP! Be natively more robust via Aliasing and Spectral Artifact free Pooling
par: Grabinski, Julia, et autres
Publié: (2023)

DispBench: Benchmarking Disparity Estimation to Synthetic Corruptions
par: Agnihotri, Shashank, et autres
Publié: (2025)

Unfolding Local Growth Rate Estimates for (Almost) Perfect Adversarial Detection
par: Lorenz, Peter, et autres
Publié: (2022)

Deepfakes: we need to re-think the concept of "real" images
par: Keuper, Janis, et autres
Publié: (2025)

Domain-Aware Fine-Tuning of Foundation Models
par: Kaplan, Ugur Ali, et autres
Publié: (2024)

Towards Fair Class-wise Robustness: Class Optimal Distribution Adversarial Training
par: Zhi, Hongxin, et autres
Publié: (2025)

FastAT Benchmark: A Comprehensive Framework for Fair Evaluation of Fast Adversarial Training Methods
par: Pan, Chao, et autres
Publié: (2026)

Is RobustBench/AutoAttack a suitable Benchmark for Adversarial Robustness?
par: Lorenz, Peter, et autres
Publié: (2021)

MEAT: Median-Ensemble Adversarial Training for Improving Robustness and Generalization
par: Hu, Zhaozhe, et autres
Publié: (2024)

Improving Fast Adversarial Training Paradigm: An Example Taxonomy Perspective
par: Gui, Jie, et autres
Publié: (2024)

Can Biases in ImageNet Models Explain Generalization?
par: Gavrikov, Paul, et autres
Publié: (2024)

CROC: Evaluating and Training T2I Metrics with Pseudo- and Human-Labeled Contrastive Robustness Checks
par: Leiter, Christoph, et autres
Publié: (2025)

What is Adversarial Training for Diffusion Models?
par: Rosaria, Briglia Maria, et autres
Publié: (2025)

Improving Adversarial Robust Fairness via Anti-Bias Soft Label Distillation
par: Zhao, Shiji, et autres
Publié: (2023)

FairDeFace: Evaluating the Fairness and Adversarial Robustness of Face Obfuscation Methods
par: Khorzooghi, Seyyed Mohammad Sadegh Moosavi, et autres
Publié: (2025)

RobustSpring: Benchmarking Robustness to Image Corruptions for Optical Flow, Scene Flow and Stereo
par: Oei, Victor, et autres
Publié: (2025)

As large as it gets: Learning infinitely large Filters via Neural Implicit Functions in the Fourier Domain
par: Grabinski, Julia, et autres
Publié: (2023)

Real-time Prediction of Urban Sound Propagation with Conditioned Normalizing Flows
par: Eckerle, Achim, et autres
Publié: (2025)

Improving Accuracy-robustness Trade-off via Pixel Reweighted Adversarial Training
par: Zhang, Jiacheng, et autres
Publié: (2024)

PeerAiD: Improving Adversarial Distillation from a Specialized Peer Tutor
par: Jung, Jaewon, et autres
Publié: (2024)

Understanding Adversarial Training with Energy-based Models
par: Mirza, Mujtaba Hussain, et autres
Publié: (2025)

Improving Adversarial Transferability via Model Alignment
par: Ma, Avery, et autres
Publié: (2023)

SemSegBench & DetecBench: Benchmarking Reliability and Generalization Beyond Classification
par: Agnihotri, Shashank, et autres
Publié: (2025)

VSTAR: Generative Temporal Nursing for Longer Dynamic Video Synthesis
par: Li, Yumeng, et autres
Publié: (2024)

Improving Feature Stability during Upsampling -- Spectral Artifacts and the Importance of Spatial Context
par: Agnihotri, Shashank, et autres
Publié: (2023)