6 citations · 9 across the 6 of their papers we have counts for
6 papers
GhostEncoder: Stealthy Backdoor Attacks with Dynamic Triggers to Pre-trained Encoders in Self-supervised Learning
Qiannan Wang, Changchun Yin, Zhe Liu +3
Within the realm of computer vision, self-supervised learning (SSL) pertains to training pre-trained image encoders utilizing a substantial quantity of unlabeled images. Pre-traine…
Hard Adversarial Example Mining for Improving Robust Fairness
Chenhao Lin, Xiang Ji, Yulong Yang +4
Adversarial training (AT) is widely considered the state-of-the-art technique for improving the robustness of deep neural networks (DNNs) against adversarial examples (AE). Neverth…
SSL-Auth: An Authentication Framework by Fragile Watermarking for Pre-trained Encoders in Self-supervised Learning
Xiaobei Li, Changchun Yin, Liyue Zhu +4
Self-supervised learning (SSL), a paradigm harnessing unlabeled datasets to train robust encoders, has recently witnessed substantial success. These encoders serve as pivotal featu…
What can Discriminator do? Towards Box-free Ownership Verification of Generative Adversarial Network
Ziheng Huang, Boheng Li, Yan Cai +5
In recent decades, Generative Adversarial Network (GAN) and its variants have achieved unprecedented success in image synthesis. However, well-trained GANs are under the threat of…
Cluster-guided Contrastive Graph Clustering Network
Xihong Yang, Yue Liu, Sihang Zhou +6
Benefiting from the intrinsic supervision information exploitation capability, contrastive learning has achieved promising performance in the field of deep graph clustering recentl…
Free Fine-tuning: A Plug-and-Play Watermarking Scheme for Deep Neural Networks
Run Wang, Jixing Ren, Boheng Li +6
Watermarking has been widely adopted for protecting the intellectual property (IP) of Deep Neural Networks (DNN) to defend the unauthorized distribution. Unfortunately, the popular…