4 papers
Self-supervised Feature Disentanglement and Augmentation Network for One-class Face Anti-spoofing
Pei-Kai Huang, Jun-Xiong Chong, Ming-Tsung Hsu +5
Face anti-spoofing (FAS) techniques aim to enhance the security of facial identity authentication by distinguishing authentic live faces from deceptive attempts. While two-class FA…
Robust Multi-Modal Face Anti-Spoofing with Domain Adaptation: Tackling Missing Modalities, Noisy Pseudo-Labels, and Model Degradation
Ming-Tsung Hsu, Fang-Yu Hsu, Yi-Ting Lin +6
Recent multi-modal face anti-spoofing (FAS) methods have investigated the potential of leveraging multiple modalities to distinguish live and spoof faces. However, pre-adapted mult…
Multi-Modal Face Anti-Spoofing via Cross-Modal Feature Transitions
Jun-Xiong Chong, Fang-Yu Hsu, Ming-Tsung Hsu +4
Multi-modal face anti-spoofing (FAS) aims to detect genuine human presence by extracting discriminative liveness cues from multiple modalities, such as RGB, infrared (IR), and dept…
Enhancing Learnable Descriptive Convolutional Vision Transformer for Face Anti-Spoofing
Pei-Kai Huanga, Jun-Xiong Chong, Ming-Tsung Hsu +2
Face anti-spoofing (FAS) heavily relies on identifying live/spoof discriminative features to counter face presentation attacks. Recently, we proposed LDCformer to successfully inco…