Face Recognition
Face recognition research aims to develop accurate and robust systems for identifying individuals from their facial images. Current efforts focus on improving performance under challenging conditions (e.g., low-resolution images, occlusions), mitigating biases stemming from demographic imbalances in training data, and enhancing the explainability and security of these systems through techniques like knowledge distillation and adversarial watermarking. These advancements have significant implications for various applications, including security, law enforcement, and healthcare, while also raising important ethical considerations regarding privacy and fairness.
Papers
Understanding Cross Domain Presentation Attack Detection for Visible Face Recognition
Jennifer Hamblin, Kshitij Nikhal, Benjamin S. Riggan
FaceQvec: Vector Quality Assessment for Face Biometrics based on ISO Compliance
Javier Hernandez-Ortega, Julian Fierrez, Luis F. Gomez, Aythami Morales, Jose Luis Gonzalez-de-Suso, Francisco Zamora-Martinez