ECCV 2024 "adversarial training" Papers
9 papers found
Catastrophic Overfitting: A Potential Blessing in Disguise
MN Zhao, Lihe Zhang, Yuqiu Kong et al.
ECCV 2024posterarXiv:2402.18211
1
citations
Enhancing Tracking Robustness with Auxiliary Adversarial Defense Networks
Zhewei Wu, Ruilong Yu, Qihe Liu et al.
ECCV 2024posterarXiv:2402.17976
4
citations
Exploiting Supervised Poison Vulnerability to Strengthen Self-Supervised Defense
Jeremy Styborski, Mingzhi Lyu, YI HUANG et al.
ECCV 2024posterarXiv:2409.08509
1
citations
Improving Domain Generalization in Self-Supervised Monocular Depth Estimation via Stabilized Adversarial Training
Yuanqi Yao, Gang Wu, Kui Jiang et al.
ECCV 2024posterarXiv:2411.02149
7
citations
Learning a Dynamic Privacy-preserving Camera Robust to Inversion Attacks
Jiacheng Cheng, Xiang Dai, Jia Wan et al.
ECCV 2024poster
1
citations
Learning Differentially Private Diffusion Models via Stochastic Adversarial Distillation
Bochao Liu, Pengju Wang, Shiming Ge
ECCV 2024posterarXiv:2408.14738
4
citations
Preventing Catastrophic Overfitting in Fast Adversarial Training: A Bi-level Optimization Perspective
Zhaoxin Wang, Handing Wang, Cong Tian et al.
ECCV 2024posterarXiv:2407.12443
8
citations
Shedding More Light on Robust Classifiers under the lens of Energy-based Models
Mujtaba Hussain Mirza, Maria Rosaria Briglia, Senad Beadini et al.
ECCV 2024posterarXiv:2407.06315
7
citations
Towards Reliable Evaluation and Fast Training of Robust Semantic Segmentation Models
Francesco Croce, Naman D. Singh, Matthias Hein
ECCV 2024posterarXiv:2306.12941
12
citations