Boosting Adversarial Transferability with a Generative Model Perspective- Author : Jongoh Jeong, Hunmin Yang, and Kuk-Jin Yoon – Published Date : 2025.06.11 – Category : Adversarial Learning, Generative Model – Place of publication : The IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) 2025 Workshop on Generative Models for Computer Vision (GMCV) Abstract: Generative…
Prompt-Driven Contrastive Learning for Transferable Adversarial Attacks- Author : Hunmin Yang, Jongoh Jeong, and Kuk-Jin Yoon – Published Date : TBD – Category : Transferable Adversarial Attacks – Place of publication : European Conference on Computer Vision (ECCV) 2024 (oral) Abstract: Recent vision-language foundation models, such as CLIP, have demonstrated superior capabilities in learning representations that can be transferable…
We have two papers accepted to the Thirty-Eighth AAAI Conference on Artificial Intelligence 2024. The papers are “FACL-Attack: Frequency-Aware Contrastive Learning for Transferable Adversarial Attacks” by Hunmin Yang*, Jongoh Jeong*, and Kuk-Jin Yoon (*equal contribution), “Improving Transferability for Cross-domain Trajectory Prediction via Neural Stochastic Differential Equation” by Daehee Park, Jaewoo Jeong, and Kuk-Jin Yoon.
FACL-Attack: Frequency-Aware Contrastive Learning for Transferable Adversarial Attacks- Author : Hunmin Yang*, Jongoh Jeong*, and Kuk-Jin Yoon (*equal contribution) – Published Date : TBD – Category : Constrastive learning – Place of publication : Thirty-Eighth AAAI Conference on Artificial Intelligence (AAAI) 2024 Abstract: Deep neural networks are known to be vulnerable to security risks due to the…