FAS24
* *ChaLearn Face Anti-Spoofing
* Advancing Cross-Domain Generalizability in Face Anti-Spoofing: Insights, Design, and Metrics
* Assessing the Performance of Efficient Face Anti-Spoofing Detection Against Physical and Digital Presentation Attacks
* IDAdapter: Learning Mixed Features for Tuning-Free Personalization of Text-to-Image Models
* Joint Physical-Digital Facial Attack Detection Via Simulating Spoofing Clues
* Multi-angle Consistent Generative NeRF with Additive Angular Margin Momentum Contrastive Learning
* Multiattention-Net: A Novel Approach to Face Anti-Spoofing with Modified Squeezed Residual Blocks
* Rethinking the Domain Gap in Near-infrared Face Recognition
* Snapshot Spectral Imaging for Face Anti-Spoofing: Addressing Data Challenges with Advanced Processing and Training
* Supervised Contrastive Learning for Snapshot Spectral Imaging Face Anti-Spoofing
* Unified Face Attack Detection with Micro Disturbance and a Two-Stage Training Strategy
* Unified Physical-Digital Attack Detection Challenge
* visualization method for data domain changes in CNN networks and the optimization method for selecting thresholds in classification tasks, A
13 for FAS24