1 citations · 2 across the 4 of their papers we have counts for
5 papers
On the Intrinsic Limited Robustness of Latent-Based Watermarking
Cheng-Han Yeh, Kuan-chun Yu, Cheng-Chang Tsai +1
Existing latent-based watermarking methods for diffusion models have overestimated their robustness to image distortions, including geometric transformations such as rotation, scal…
FedSDA: Federated Stain Distribution Alignment for Non-IID Histopathological Image Classification
Cheng-Chang Tsai, Kai-Wen Cheng, Chun-Shien Lu
Federated learning (FL) has shown success in collaboratively training a model among decentralized data resources without directly sharing privacy-sensitive training data. Despite r…
MaXsive: High-Capacity and Robust Training-Free Generative Image Watermarking in Diffusion Models
Po-Yuan Mao, Cheng-Chang Tsai, Chun-Shien Lu
The great success of the diffusion model in image synthesis led to the release of gigantic commercial models, raising the issue of copyright protection and inappropriate content ge…
Adversarial Robustness Overestimation and Instability in TRADES
Jonathan Weiping Li, Ren-Wei Liang, Cheng-Han Yeh +4
This paper examines the phenomenon of probabilistic robustness overestimation in TRADES, a prominent adversarial training method. Our study reveals that TRADES sometimes yields dis…
BadVim: Unveiling Backdoor Threats in Visual State Space Model
Cheng-Yi Lee, Yu-Hsuan Chiang, Zhong-You Wu +2
Visual State Space Models (VSSM) have shown remarkable performance in various computer vision tasks. However, backdoor attacks pose significant security challenges, causing comprom…