98 citations · 218 across the 6 of their papers we have counts for
6 papers
Towards Data-Centric Face Anti-Spoofing: Improving Cross-domain Generalization via Physics-based Data Synthesis
Rizhao Cai, Cecelia Soh, Zitong Yu +3
Face Anti-Spoofing (FAS) research is challenged by the cross-domain problem, where there is a domain gap between the training and testing data. While recent FAS works are mainly mo…
Rehearsal-Free Domain Continual Face Anti-Spoofing: Generalize More and Forget Less
Rizhao Cai, Yawen Cui, Zhi Li +4
Face Anti-Spoofing (FAS) is recently studied under the continual learning setting, where the FAS models are expected to evolve after encountering the data from new domains. However…
Toward domain generalized pruning by scoring out-of-distribution importance
Rizhao Cai, Haoliang Li, Alex Kot
Filter pruning has been widely used for compressing convolutional neural networks to reduce computation costs during the deployment stage. Recent studies have shown that filter pru…
Learning Meta Pattern for Face Anti-Spoofing
Rizhao Cai, Zhi Li, Renjie Wan +3
Face Anti-Spoofing (FAS) is essential to secure face recognition systems and has been extensively studied in recent years. Although deep neural networks (DNNs) for the FAS task hav…
DRL-FAS: A Novel Framework Based on Deep Reinforcement Learning for Face Anti-Spoofing
Rizhao Cai, Haoliang Li, Shiqi Wang +2
Inspired by the philosophy employed by human beings to determine whether a presented face example is genuine or not, i.e., to glance at the example globally first and then carefull…
Multi-task Mid-level Feature Alignment Network for Unsupervised Cross-Dataset Person Re-Identification
Shan Lin, Haoliang Li, Chang-Tsun Li +1
Most existing person re-identification (Re-ID) approaches follow a supervised learning framework, in which a large number of labelled matching pairs are required for training. Such…