99 citations · 361 across the 41 of their papers we have counts for
13 papers · 1 filter
Exploiting Fine-grained Face Forgery Clues via Progressive Enhancement Learning
Qiqi Gu, Shen Chen, Taiping Yao +3
With the rapid development of facial forgery techniques, forgery detection has attracted more and more attention due to security concerns. Existing approaches attempt to use freque…
Dual Contrastive Learning for General Face Forgery Detection
Ke Sun, Taiping Yao, Shen Chen +3
With various facial manipulation techniques arising, face forgery detection has drawn growing attention due to security concerns. Previous works always formulate face forgery detec…
Reciprocal Normalization for Domain Adaptation
Zhiyong Huang, Kekai Sheng, Ke Li +5
Batch normalization (BN) is widely used in modern deep neural networks, which has been shown to represent the domain-related knowledge, and thus is ineffective for cross-domain tas…
Spatiotemporal Inconsistency Learning for DeepFake Video Detection
Zhihao Gu, Yang Chen, Taiping Yao +4
The rapid development of facial manipulation techniques has aroused public concerns in recent years. Following the success of deep learning, existing methods always formulate DeepF…
Adaptive Normalized Representation Learning for Generalizable Face Anti-Spoofing
Shubao Liu, Ke-Yue Zhang, Taiping Yao +5
With various face presentation attacks arising under unseen scenarios, face anti-spoofing (FAS) based on domain generalization (DG) has drawn growing attention due to its robustnes…
Structure Destruction and Content Combination for Face Anti-Spoofing
Ke-Yue Zhang, Taiping Yao, Jian Zhang +4
In pursuit of consolidating the face verification systems, prior face anti-spoofing studies excavate the hidden cues in original images to discriminate real persons and diverse att…
Dual Reweighting Domain Generalization for Face Presentation Attack Detection
Shubao Liu, Ke-Yue Zhang, Taiping Yao +6
Face anti-spoofing approaches based on domain generalization (DG) have drawn growing attention due to their robustness for unseen scenarios. Previous methods treat each sample from…
Adv-Makeup: A New Imperceptible and Transferable Attack on Face Recognition
Bangjie Yin, Wenxuan Wang, Taiping Yao +5
Deep neural networks, particularly face recognition models, have been shown to be vulnerable to both digital and physical adversarial examples. However, existing adversarial exampl…
Local Relation Learning for Face Forgery Detection
Shen Chen, Taiping Yao, Yang Chen +3
With the rapid development of facial manipulation techniques, face forgery detection has received considerable attention in digital media forensics due to security concerns. Most e…
Generalizable Representation Learning for Mixture Domain Face Anti-Spoofing
Zhihong Chen, Taiping Yao, Kekai Sheng +5
Face anti-spoofing approach based on domain generalization(DG) has drawn growing attention due to its robustness forunseen scenarios. Existing DG methods assume that the do-main la…
Delving into Data: Effectively Substitute Training for Black-box Attack
Wenxuan Wang, Bangjie Yin, Taiping Yao +6
Deep models have shown their vulnerability when processing adversarial samples. As for the black-box attack, without access to the architecture and weights of the attacked model, t…
DeeperForensics Challenge 2020 on Real-World Face Forgery Detection: Methods and Results
Liming Jiang, Zhengkui Guo, Wayne Wu +18
This paper reports methods and results in the DeeperForensics Challenge 2020 on real-world face forgery detection. The challenge employs the DeeperForensics-1.0 dataset, one of the…
Aurora Guard: Reliable Face Anti-Spoofing via Mobile Lighting System
Jian Zhang, Ying Tai, Taiping Yao +6
Face authentication on mobile end has been widely applied in various scenarios. Despite the increasing reliability of cutting-edge face authentication/verification systems to varia…