5 citations · 20 across the 11 of their papers we have counts for
11 papers
DeepFake-Adapter: Dual-Level Adapter for DeepFake Detection
Rui Shao, Tianxing Wu, Liqiang Nie +1
Existing deepfake detection methods fail to generalize well to unseen or degraded samples, which can be attributed to the over-fitting of low-level forgery patterns. Here we argue…
Detecting and Grounding Multi-Modal Media Manipulation
Rui Shao, Tianxing Wu, Ziwei Liu
Misinformation has become a pressing issue. Fake media, in both visual and textual forms, is widespread on the web. While various deepfake detection and text fake news detection me…
Mixup for Test-Time Training
Bochao Zhang, Rui Shao, Jingda Du +1
Test-time training provides a new approach solving the problem of domain shift. In its framework, a test-time training phase is inserted between training phase and test phase. Duri…
Detecting and Recovering Sequential DeepFake Manipulation
Rui Shao, Tianxing Wu, Ziwei Liu
Since photorealistic faces can be readily generated by facial manipulation technologies nowadays, potential malicious abuse of these technologies has drawn great concerns. Numerous…
Open-set Adversarial Defense with Clean-Adversarial Mutual Learning
Rui Shao, Pramuditha Perera, Pong C. Yuen +1
Open-set recognition and adversarial defense study two key aspects of deep learning that are vital for real-world deployment. The objective of open-set recognition is to identify s…
Federated Test-Time Adaptive Face Presentation Attack Detection with Dual-Phase Privacy Preservation
Rui Shao, Bochao Zhang, Pong C. Yuen +1
Face presentation attack detection (fPAD) plays a critical role in the modern face recognition pipeline. The generalization ability of face presentation attack detection models to…
Federated Generalized Face Presentation Attack Detection
Rui Shao, Pramuditha Perera, Pong C. Yuen +1
Face presentation attack detection plays a critical role in the modern face recognition pipeline. A face presentation attack detection model with good generalization can be obtaine…
Expanding Semantic Knowledge for Zero-shot Graph Embedding
Zheng Wang, Ruihang Shao, Changping Wang +3
Zero-shot graph embedding is a major challenge for supervised graph learning. Although a recent method RECT has shown promising performance, its working mechanisms are not clear an…
Open-set Adversarial Defense
Rui Shao, Pramuditha Perera, Pong C. Yuen +1
Open-set recognition and adversarial defense study two key aspects of deep learning that are vital for real-world deployment. The objective of open-set recognition is to identify s…
Federated Face Presentation Attack Detection
Rui Shao, Pramuditha Perera, Pong C. Yuen +1
Face presentation attack detection (fPAD) plays a critical role in the modern face recognition pipeline. A face presentation attack detection model with good generalization can be…
Regularized Fine-grained Meta Face Anti-spoofing
Rui Shao, Xiangyuan Lan, Pong C. Yuen
Face presentation attacks have become an increasingly critical concern when face recognition is widely applied. Many face anti-spoofing methods have been proposed, but most of them…