Fine-tuning visual models has been widely shown promising performance on many
downstream visual tasks. With the surprising development of pre-trained visual foundation …

Multimodal image fusion aims to integrate information from different imaging techniques to
produce a comprehensive, detail-rich single image for downstream vision tasks. Existing …

Abstract Face Anti-Spoofing (FAS) is recently studied under the continual learning setting,
where the FAS models are expected to evolve after encountering data from new domains …

Face anti-spoofing (FAS) plays a vital role in securing face recognition systems from
presentation attacks. Benefitted from the maturing camera sensors, single-modal (RGB) and …

With the growing popularity of facial recognition (FR) in access control systems, there has
been a corresponding increase in presentation attacks (PAs) to gain unauthorized access …

Recently, vision transformer based multimodal learning methods have been proposed to
improve the robustness of face anti-spoofing (FAS) systems. However, multimodal face data …

The generalizable face anti-spoofing (FAS) has attracted much attention recently. Even
though many existing methods perform well under intra-domain settings, the model's …

Abstract The effectiveness of Vision Transformers (ViTs) diminishes considerably in multi-
modal face anti-spoofing (FAS) under missing modality scenarios. Existing approaches rely …

Multimodal face anti-spoofing systems adopt multiple sensor modalities, such as infrared,
color, depth, and thermal, to distinguish between living and spoofing faces via …

Face presentation attack detection (PAD) plays a pivotal role in securing face recognition
systems against spoofing attacks. Although great progress has been made in designing face …