48 citations · 62 across the 17 of their papers we have counts for
14 papers · 1 filter
Improving Adversarial Robustness via Decoupled Visual Representation Masking
Decheng Liu, Tao Chen, Chunlei Peng +3
Deep neural networks are proven to be vulnerable to fine-designed adversarial examples, and adversarial defense algorithms draw more and more attention nowadays. Pre-processing bas…
Imperceptible Face Forgery Attack via Adversarial Semantic Mask
Decheng Liu, Qixuan Su, Chunlei Peng +2
With the great development of generative model techniques, face forgery detection draws more and more attention in the related field. Researchers find that existing face forgery mo…
Adv-Diffusion: Imperceptible Adversarial Face Identity Attack via Latent Diffusion Model
Decheng Liu, Xijun Wang, Chunlei Peng +3
Adversarial attacks involve adding perturbations to the source image to cause misclassification by the target model, which demonstrates the potential of attacking face recognition…
Gradient constrained sharpness-aware prompt learning for vision-language models
Liangchen Liu, Nannan Wang, Dawei Zhou +4
This paper targets a novel trade-off problem in generalizable prompt learning for vision-language models (VLM), i.e., improving the performance on unseen classes while maintaining…
Attention Consistency Refined Masked Frequency Forgery Representation for Generalizing Face Forgery Detection
Decheng Liu, Tao Chen, Chunlei Peng +3
Due to the successful development of deep image generation technology, visual data forgery detection would play a more important role in social and economic security. Existing forg…
PRO-Face S: Privacy-preserving Reversible Obfuscation of Face Images via Secure Flow
Lin Yuan, Kai Liang, Xiao Pu +5
This paper proposes a novel paradigm for facial privacy protection that unifies multiple characteristics including anonymity, diversity, reversibility and security within a single…