5 citations · 11 across the 7 of their papers we have counts for
7 papers
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…
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…
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…